From 7ad235965ff85f8552359e01341331bb44e02fcb Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Zden=C4=9Bk=20Lape=C5=A1?= Date: Mon, 27 Apr 2026 17:05:11 +0200 Subject: [PATCH 1/6] feat(transformers): add uv-based model runners --- .gitignore | 2 + .python-version | 1 + pyproject.toml | 17 + scripts/uv.sh | 16 + transformers/README.md | 119 +- transformers/base.py | 89 +- ...liquid_450m_example.sh => LFM2-VL-1.6B.sh} | 7 +- .../{qwen3_2b_example.sh => LFM2-VL-3B.sh} | 7 +- ...liquid_1.6b_example.sh => LFM2-VL-450M.sh} | 7 +- transformers/examples/LFM2.5-VL-1.6B.sh | 19 + transformers/examples/LFM2.5-VL-450M.sh | 19 + transformers/examples/Qwen3-VL-2B-Instruct.sh | 19 + transformers/examples/Qwen3-VL-4B-Instruct.sh | 19 + .../{gemma_example.sh => gemma-3-4b-it.sh} | 7 +- transformers/examples/gemma-3-4b-pt.sh | 20 + transformers/examples/gemma-4-E2B-it.sh | 20 + transformers/examples/gemma_example_simple.sh | 8 - transformers/examples/qwen3_4b_example.sh | 18 - transformers/models/LFM2-VL-1.6B/run.py | 56 + transformers/models/LFM2-VL-3B/run.py | 56 + transformers/models/LFM2-VL-450M/run.py | 2 +- transformers/models/LFM2.5-VL-1.6B/run.py | 65 +- transformers/models/LFM2.5-VL-450M/run.py | 97 ++ .../models/Qwen3-VL-2B-Instruct/run.py | 2 +- .../models/Qwen3-VL-4B-Instruct/run.py | 21 +- transformers/models/gemma-3-4b-it/run.py | 2 +- transformers/models/gemma-3-4b-pt/run.py | 54 + transformers/models/gemma-4-E2B-it/run.py | 54 + uv.lock | 1228 +++++++++++++++++ 29 files changed, 1911 insertions(+), 140 deletions(-) create mode 100644 .python-version create mode 100644 pyproject.toml create mode 100644 scripts/uv.sh rename transformers/examples/{liquid_450m_example.sh => LFM2-VL-1.6B.sh} (69%) mode change 100755 => 100644 rename transformers/examples/{qwen3_2b_example.sh => LFM2-VL-3B.sh} (70%) mode change 100755 => 100644 rename transformers/examples/{liquid_1.6b_example.sh => LFM2-VL-450M.sh} (69%) mode change 100755 => 100644 create mode 100644 transformers/examples/LFM2.5-VL-1.6B.sh create mode 100644 transformers/examples/LFM2.5-VL-450M.sh create mode 100644 transformers/examples/Qwen3-VL-2B-Instruct.sh create mode 100644 transformers/examples/Qwen3-VL-4B-Instruct.sh rename transformers/examples/{gemma_example.sh => gemma-3-4b-it.sh} (70%) mode change 100755 => 100644 create mode 100644 transformers/examples/gemma-3-4b-pt.sh create mode 100644 transformers/examples/gemma-4-E2B-it.sh delete mode 100755 transformers/examples/gemma_example_simple.sh delete mode 100755 transformers/examples/qwen3_4b_example.sh create mode 100644 transformers/models/LFM2-VL-1.6B/run.py create mode 100644 transformers/models/LFM2-VL-3B/run.py create mode 100644 transformers/models/LFM2.5-VL-450M/run.py create mode 100644 transformers/models/gemma-3-4b-pt/run.py create mode 100644 transformers/models/gemma-4-E2B-it/run.py create mode 100644 uv.lock diff --git a/.gitignore b/.gitignore index 8e8c96c..5c9bf99 100644 --- a/.gitignore +++ b/.gitignore @@ -12,3 +12,5 @@ __pycache__/ # OS .DS_Store +.env +.idea/ diff --git a/.python-version b/.python-version new file mode 100644 index 0000000..e4fba21 --- /dev/null +++ b/.python-version @@ -0,0 +1 @@ +3.12 diff --git a/pyproject.toml b/pyproject.toml new file mode 100644 index 0000000..ee23cac --- /dev/null +++ b/pyproject.toml @@ -0,0 +1,17 @@ +[project] +name = "vlm-scripts" +version = "0.1.0" +requires-python = ">=3.12" +dependencies = [ + "accelerate>=1.12.0", + "numpy<2; sys_platform == 'darwin' and platform_machine == 'x86_64'", + "peft>=0.18.1", + "pillow>=10.0", + "safetensors>=0.7.0", + "torch==2.2.2; sys_platform == 'darwin' and platform_machine == 'x86_64'", + "torch>=2.10.0; sys_platform != 'darwin' or platform_machine != 'x86_64'", + "transformers==5.0.0; sys_platform == 'darwin' and platform_machine == 'x86_64'", + "transformers>=5.1.0; sys_platform != 'darwin' or platform_machine != 'x86_64'", + "torchvision==0.17.2; sys_platform == 'darwin' and platform_machine == 'x86_64'", + "torchvision>=0.26.0; sys_platform != 'darwin' or platform_machine != 'x86_64'", +] diff --git a/scripts/uv.sh b/scripts/uv.sh new file mode 100644 index 0000000..17bcbbf --- /dev/null +++ b/scripts/uv.sh @@ -0,0 +1,16 @@ +#!/bin/bash + +# THIS SCRIPT IS NOT INTENDED TO BE RUN DIRECTLY, BUT RATHER AS A TEMPLATE FOR RUNNING THE INDIVIDUAL SCRIPTS + +uv run transformers/models/Qwen3-VL-2B-Instruct/run.py \ + --model_path $HOME/Downloads/model/ \ + --images $HOME/Downloads/google.webp \ + --user_prompt "Describe this image." \ + --system_prompt "You are a helpful assistant for answering questions about the image. Answer in detail and be as descriptive as possible." + +uv run transformers/models/LFM2.5-VL-1.6B/run.py \ + --model_path $HOME/Downloads/model/ \ + --images $HOME/Downloads/google.webp \ + --device cpu \ + --user_prompt "Describe this image." \ + --system_prompt "You are a helpful assistant for answering questions about the image. Answer in detail and be as descriptive as possible." diff --git a/transformers/README.md b/transformers/README.md index b64a874..93568a3 100644 --- a/transformers/README.md +++ b/transformers/README.md @@ -12,13 +12,18 @@ The scripts auto-detect the format from the model directory and handle all three ## Supported Models -| Model | Script | Base Model (HuggingFace) | -|---|---|---| -| LiquidAI LFM2-VL-450M | [models/LFM2-VL-450M/run.py](models/LFM2-VL-450M/run.py) | [LiquidAI/LFM2-VL-450M](https://huggingface.co/LiquidAI/LFM2-VL-450M) | -| LiquidAI LFM2.5-VL-1.6B | [models/LFM2.5-VL-1.6B/run.py](models/LFM2.5-VL-1.6B/run.py) | [LiquidAI/LFM2.5-VL-1.6B](https://huggingface.co/LiquidAI/LFM2.5-VL-1.6B) | -| Google Gemma 3 4B | [models/gemma-3-4b-it/run.py](models/gemma-3-4b-it/run.py) | [google/gemma-3-4b-it](https://huggingface.co/google/gemma-3-4b-it) | -| Qwen3-VL 2B | [models/Qwen3-VL-2B-Instruct/run.py](models/Qwen3-VL-2B-Instruct/run.py) | [Qwen/Qwen3-VL-2B-Instruct](https://huggingface.co/Qwen/Qwen3-VL-2B-Instruct) | -| Qwen3-VL 4B | [models/Qwen3-VL-4B-Instruct/run.py](models/Qwen3-VL-4B-Instruct/run.py) | [Qwen/Qwen3-VL-4B-Instruct](https://huggingface.co/Qwen/Qwen3-VL-4B-Instruct) | +| Model | Script | Base Model (HuggingFace) | +|-------------------------|--------------------------------------------------------------------------|-------------------------------------------------------------------------------| +| LiquidAI LFM2-VL-450M | [models/LFM2-VL-450M/run.py](models/LFM2-VL-450M/run.py) | [LiquidAI/LFM2-VL-450M](https://huggingface.co/LiquidAI/LFM2-VL-450M) | +| LiquidAI LFM2-VL-1.6B | [models/LFM2-VL-1.6B/run.py](models/LFM2-VL-1.6B/run.py) | [LiquidAI/LFM2-VL-1.6B](https://huggingface.co/LiquidAI/LFM2-VL-1.6B) | +| LiquidAI LFM2-VL-3B | [models/LFM2-VL-3B/run.py](models/LFM2-VL-3B/run.py) | [LiquidAI/LFM2-VL-3B](https://huggingface.co/LiquidAI/LFM2-VL-3B) | +| LiquidAI LFM2.5-VL-450M | [models/LFM2.5-VL-450M/run.py](models/LFM2.5-VL-450M/run.py) | [LiquidAI/LFM2.5-VL-450M](https://huggingface.co/LiquidAI/LFM2.5-VL-450M) | +| LiquidAI LFM2.5-VL-1.6B | [models/LFM2.5-VL-1.6B/run.py](models/LFM2.5-VL-1.6B/run.py) | [LiquidAI/LFM2.5-VL-1.6B](https://huggingface.co/LiquidAI/LFM2.5-VL-1.6B) | +| Google Gemma 3 4B PT | [models/gemma-3-4b-pt/run.py](models/gemma-3-4b-pt/run.py) | [google/gemma-3-4b-pt](https://huggingface.co/google/gemma-3-4b-pt) | +| Google Gemma 3 4B | [models/gemma-3-4b-it/run.py](models/gemma-3-4b-it/run.py) | [google/gemma-3-4b-it](https://huggingface.co/google/gemma-3-4b-it) | +| Google Gemma 4 E2B | [models/gemma-4-E2B-it/run.py](models/gemma-4-E2B-it/run.py) | [google/gemma-4-E2B-it](https://huggingface.co/google/gemma-4-E2B-it) | +| Qwen3-VL 2B | [models/Qwen3-VL-2B-Instruct/run.py](models/Qwen3-VL-2B-Instruct/run.py) | [Qwen/Qwen3-VL-2B-Instruct](https://huggingface.co/Qwen/Qwen3-VL-2B-Instruct) | +| Qwen3-VL 4B | [models/Qwen3-VL-4B-Instruct/run.py](models/Qwen3-VL-4B-Instruct/run.py) | [Qwen/Qwen3-VL-4B-Instruct](https://huggingface.co/Qwen/Qwen3-VL-4B-Instruct) | ## Requirements @@ -27,14 +32,14 @@ The scripts auto-detect the format from the model directory and handle all three ### Library versions -| Library | Version | -|---|---| -| torch | >= 2.10.0 | -| transformers | >= 5.1.0 | -| peft | >= 0.18.1 | -| accelerate | >= 1.12.0 | -| safetensors | >= 0.7.0 | -| pillow | >= 10.0 | +| Library | Version | +|--------------|-----------| +| torch | >= 2.10.0 | +| transformers | >= 5.1.0 | +| peft | >= 0.18.1 | +| accelerate | >= 1.12.0 | +| safetensors | >= 0.7.0 | +| pillow | >= 10.0 | ## Setup @@ -94,6 +99,14 @@ python models/LFM2.5-VL-1.6B/run.py \ --user_prompt "Describe this image." ``` +On Apple Silicon, `LiquidAI/LFM2.5-VL-*` models require explicit MPS CPU fallback opt-in before Python starts: + +```bash +PYTORCH_ENABLE_MPS_FALLBACK=1 python models/LFM2.5-VL-1.6B/run.py \ + --model_path /path/to/your/model \ + --images photo.jpg +``` + ### With URL images and system prompt ```bash @@ -130,30 +143,35 @@ This prints token counts, input tensor shapes, generation time, and tokens/sec. ### Arguments -| Argument | Required | Default | Description | -|---|---|---|---| -| `--model_path` | Yes | - | Path to your downloaded model directory | -| `--images` | No | none | One or more image file paths or URLs | -| `--user_prompt` | No | "Describe this image." | Text prompt for the model | -| `--system_prompt` | No | None | System instruction (optional) | -| `--max_tokens` | No | per model | Maximum tokens to generate | -| `--temperature` | No | per model | Sampling temperature (0.0 = greedy) | -| `--device` | No | auto | Device: auto, cpu, cuda, cuda:0, mps | -| `--dtype` | No | auto | Dtype: auto, float32, float16, bfloat16 | -| `--resize` | No | None | Max image resolution — downscale proportionally | -| `--debug` | No | off | Show token counts, timing, and input details | +| Argument | Required | Default | Description | +|-------------------|----------|------------------------|-------------------------------------------------| +| `--model_path` | Yes | - | Path to your downloaded model directory | +| `--images` | No | none | One or more image file paths or URLs | +| `--user_prompt` | No | "Describe this image." | Text prompt for the model | +| `--system_prompt` | No | None | System instruction (optional) | +| `--max_tokens` | No | per model | Maximum tokens to generate | +| `--temperature` | No | per model | Sampling temperature (0.0 = greedy) | +| `--device` | No | auto | Device: auto, cpu, cuda, cuda:0, mps | +| `--dtype` | No | auto | Dtype: auto, float32, float16, bfloat16 | +| `--resize` | No | None | Max image resolution — downscale proportionally | +| `--debug` | No | off | Show token counts, timing, and input details | ### Default generation parameters Each model has sensible defaults from its HuggingFace config. You can override them with `--max_tokens` and `--temperature`. -| Model | max_tokens | temperature | Notes | -|---|---|---|---| -| LFM2-VL-450M | 256 | 0.0 (greedy) | No sampling defaults in HF config | -| LFM2.5-VL-1.6B | 256 | 0.0 (greedy) | No sampling defaults in HF config | -| gemma-3-4b-it | 256 | 0.0 (greedy) | HF default is 1.0 but causes issues in float16 | -| Qwen3-VL-2B-Instruct | 256 | 0.7 | HF: do_sample=True, top_p=0.8, top_k=20 | -| Qwen3-VL-4B-Instruct | 256 | 0.7 | HF: do_sample=True, top_p=0.8, top_k=20 | +| Model | max_tokens | temperature | Notes | +|----------------------|------------|--------------|------------------------------------------------| +| LFM2-VL-450M | 256 | 0.0 (greedy) | No sampling defaults in HF config | +| LFM2-VL-1.6B | 256 | 0.0 (greedy) | Falls back to script defaults | +| LFM2-VL-3B | 256 | 0.0 (greedy) | Falls back to script defaults | +| LFM2.5-VL-450M | 256 | 0.0 (greedy) | Falls back to script defaults | +| LFM2.5-VL-1.6B | 256 | 0.0 (greedy) | No sampling defaults in HF config | +| gemma-3-4b-pt | 256 | 0.0 (greedy) | Falls back to script defaults | +| gemma-3-4b-it | 256 | 0.0 (greedy) | HF default is 1.0 but causes issues in float16 | +| gemma-4-E2B-it | 256 | 0.0 (greedy) | Falls back to script defaults | +| Qwen3-VL-2B-Instruct | 256 | 0.7 | HF: do_sample=True, top_p=0.8, top_k=20 | +| Qwen3-VL-4B-Instruct | 256 | 0.7 | HF: do_sample=True, top_p=0.8, top_k=20 | ## How it works @@ -169,11 +187,11 @@ The base model (for LoRA) is automatically cached in `~/.cache/huggingface/hub` Each model family handles images differently: -| Model | Image handling | -|---|---| +| Model | Image handling | +|--------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------| | **Liquid (LFM2/LFM2.5)** | Image tiling (`do_image_splitting`) with token budget (`min_image_tokens`, `max_image_tokens`). Splits large images into tiles for better detail. | -| **Gemma 3** | Fixed resolution, no tiling. | -| **Qwen3-VL** | Dynamic resolution — images are rescaled to fit within a pixel budget while preserving aspect ratio. | +| **Gemma 3** | Fixed resolution, no tiling. | +| **Qwen3-VL** | Dynamic resolution — images are rescaled to fit within a pixel budget while preserving aspect ratio. | **Important**: Your model's training settings are always respected. If your model was trained with `do_image_splitting=False`, the script detects this from the saved `preprocessor_config.json` and does not override it. Default processor kwargs (like tiling) are only applied when the model's own config doesn't specify them. @@ -188,15 +206,16 @@ RuntimeError: probability tensor contains either `inf`, `nan` or element < 0 This is a known issue with Gemma 3 models caused by multiple bugs in the transformers library: - **SDPA attention + padding** produces NaN on CPU/MPS. Fix: we use `attn_implementation="eager"` by default. -- **float16 overflow** in RMSNorm layers. Fix: we use `bfloat16` by default, which matches the model's training precision. +- **float16 overflow** in RMSNorm layers. Fix: on CUDA/CPU we use `bfloat16` by default, which matches the model's training precision. On MPS, the scripts fall back to `float16` because `bfloat16` is not universally supported there. - **float32 embedding scale mismatch** — the model was trained with bfloat16-rounded scale values, so float32 produces slightly different logits that accumulate into NaN. If you still see this error, try: + ```bash # Force greedy decoding (no sampling) --temperature 0.0 -# Or force bfloat16 explicitly +# Or force bfloat16 explicitly (CUDA/CPU only) --dtype bfloat16 ``` @@ -208,13 +227,26 @@ RuntimeError: Invalid buffer size: 8.01 GiB MPS cannot allocate large contiguous memory blocks. The scripts load models on CPU first, then move to MPS incrementally. However, larger models (4B+) may still exceed available GPU memory. +### LFM2.5 on Apple Silicon: explicit MPS fallback required + +`LiquidAI/LFM2.5-VL-*` models can hit MPS -> CPU fallback ops during image preprocessing. The scripts no longer enable that fallback automatically. + +If you want to run those models on MPS, set the env var yourself before Python starts: + +```bash +PYTORCH_ENABLE_MPS_FALLBACK=1 python models/LFM2.5-VL-1.6B/run.py ... +``` + +If you do not want MPS, pass `--device cpu`. + Workarounds: + ```bash # Run on CPU instead (slower but works) --device cpu -# Use bfloat16 to halve memory (default) ---dtype bfloat16 +# MPS uses float16 by default because bfloat16 is not always supported +--dtype float16 ``` **Recommended**: Models up to ~2B parameters work well on MPS. For 4B+ models, use CPU or a CUDA GPU. @@ -224,6 +256,7 @@ Workarounds: Generation on MPS can appear stuck for larger models — it's not frozen, just slow. Vision models are especially heavy because the image encoder runs before text generation. Tips: + - Use `--resize 384` to reduce image size and speed up processing - Use `--max_tokens 50` for quick tests - Use `--device cpu` which can be faster than MPS for some model sizes @@ -237,6 +270,7 @@ OSError: google/gemma-3-4b-it does not appear to have a file named model.safeten This means HuggingFace authentication failed. The error message is misleading — the files exist but you don't have access. See the [HuggingFace authentication](#huggingface-authentication-required-for-some-models) section above. Common causes: + - `HF_TOKEN` not set in your shell - Token is a **fine-grained** token without read access — use a **Read** token instead - License not accepted on the model's HuggingFace page @@ -250,6 +284,7 @@ Gemma 3 (4B parameters) with a LoRA adapter on CPU is very slow — expect **5-1 3. The vision encoder processes pixel values before text generation For faster results: + - Use a **CUDA GPU** (`--device cuda`) — this is how Gemma 3 is meant to run - Use **Liquid LFM2-VL-450M** on CPU — 10x smaller and much faster - Use `--resize 384` to reduce image processing time diff --git a/transformers/base.py b/transformers/base.py index fe87e93..03a76b8 100644 --- a/transformers/base.py +++ b/transformers/base.py @@ -15,6 +15,27 @@ import torch from PIL import Image + + +def _patch_torch_autocast_compat(torch_module=None) -> bool: + """Make older torch builds accept the newer transformers autocast call style.""" + torch_module = torch if torch_module is None else torch_module + + try: + torch_module.is_autocast_enabled("cpu") + return False + except TypeError: + original = torch_module.is_autocast_enabled + + def is_autocast_enabled(device_type=None): + return original() + + torch_module.is_autocast_enabled = is_autocast_enabled + return True + + +_patch_torch_autocast_compat() + from transformers import AutoModelForImageTextToText, AutoProcessor from transformers.image_utils import load_image @@ -24,7 +45,6 @@ for _name in ("httpx", "httpcore", "urllib3", "huggingface_hub.file_download"): logging.getLogger(_name).setLevel(logging.WARNING) - # --------------------------------------------------------------------------- # Default generation parameters per model # --------------------------------------------------------------------------- @@ -34,23 +54,23 @@ MODEL_DEFAULTS = { "LiquidAI/LFM2-VL-450M": { "max_tokens": 256, - "temperature": 0.0, # greedy (no sampling defaults in HF config) + "temperature": 0.0, # greedy (no sampling defaults in HF config) }, "LiquidAI/LFM2.5-VL-1.6B": { "max_tokens": 256, - "temperature": 0.0, # greedy (no sampling defaults in HF config) + "temperature": 0.0, # greedy (no sampling defaults in HF config) }, "google/gemma-3-4b-it": { "max_tokens": 256, - "temperature": 0.0, # greedy — HF default (1.0) causes nan in float16 on MPS + "temperature": 0.0, # greedy — HF default (1.0) causes nan in float16 on MPS }, "Qwen/Qwen3-VL-2B-Instruct": { "max_tokens": 256, - "temperature": 0.7, # HF default: do_sample=True, top_p=0.8, top_k=20 + "temperature": 0.7, # HF default: do_sample=True, top_p=0.8, top_k=20 }, "Qwen/Qwen3-VL-4B-Instruct": { "max_tokens": 256, - "temperature": 0.7, # HF default: do_sample=True, top_p=0.8, top_k=20 + "temperature": 0.7, # HF default: do_sample=True, top_p=0.8, top_k=20 }, } @@ -125,7 +145,7 @@ def resolve_device(device: str) -> str: } -def resolve_dtype(device: str, dtype: str = "auto") -> torch.dtype: +def resolve_dtype(device: str, dtype: str = "auto", model_id: Optional[str] = None) -> torch.dtype: """Pick the optimal dtype for the given device, or use explicit override. When dtype is "auto": @@ -136,6 +156,7 @@ def resolve_dtype(device: str, dtype: str = "auto") -> torch.dtype: Args: device: Device string (e.g. "cuda", "cpu", "mps"). dtype: Explicit dtype string or "auto" to resolve from device. + model_id: Optional HuggingFace model ID for model-specific dtype quirks. Returns: Resolved torch.dtype. @@ -195,9 +216,9 @@ def load_images(sources: List[str], max_size: Optional[int] = None) -> List[Imag def build_messages( - images: List[Image.Image], - user_prompt: str, - system_prompt: Optional[str] = None, + images: List[Image.Image], + user_prompt: str, + system_prompt: Optional[str] = None, ) -> list: """Build chat messages in OpenAI format with PIL images. @@ -233,17 +254,17 @@ def build_messages( def print_config( - model_id: str, - model_path: str, - processor, - images: List[Image.Image], - device: str, - dtype: torch.dtype, - max_tokens: int, - temperature: float, - resize: Optional[int], - user_prompt: str, - system_prompt: Optional[str], + model_id: str, + model_path: str, + processor, + images: List[Image.Image], + device: str, + dtype: torch.dtype, + max_tokens: int, + temperature: float, + resize: Optional[int], + user_prompt: str, + system_prompt: Optional[str], ) -> None: """Print a summary of all inference parameters before running the model. @@ -269,7 +290,7 @@ def print_config( # ANSI color codes for terminal output G = "\033[32m" # green C = "\033[36m" # cyan - R = "\033[0m" # reset + R = "\033[0m" # reset def kv(key: str, value: object) -> str: """Format a key-value line with green key.""" @@ -388,11 +409,11 @@ def _filter_processor_kwargs(processor_kwargs: dict, model_path: str) -> dict: def load_model( - model_id: str, - model_path: str, - device: str, - dtype: torch.dtype, - processor_kwargs: Optional[dict] = None, + model_id: str, + model_path: str, + device: str, + dtype: torch.dtype, + processor_kwargs: Optional[dict] = None, ) -> Tuple: """Load a model (full or LoRA) and its processor. @@ -506,13 +527,13 @@ def load_model( def run_inference( - model, - processor, - messages: list, - images: List[Image.Image], - max_tokens: int = 256, - temperature: float = 0.0, - debug: bool = False, + model, + processor, + messages: list, + images: List[Image.Image], + max_tokens: int = 256, + temperature: float = 0.0, + debug: bool = False, ) -> str: """Run inference on a loaded model and return the generated text. diff --git a/transformers/examples/liquid_450m_example.sh b/transformers/examples/LFM2-VL-1.6B.sh old mode 100755 new mode 100644 similarity index 69% rename from transformers/examples/liquid_450m_example.sh rename to transformers/examples/LFM2-VL-1.6B.sh index 9794c7a..bcd2cc8 --- a/transformers/examples/liquid_450m_example.sh +++ b/transformers/examples/LFM2-VL-1.6B.sh @@ -1,8 +1,9 @@ #!/bin/bash -# Example: Run LiquidAI LFM2-VL-450M with a LoRA adapter +# Example: Run LiquidAI/LFM2-VL-1.6B with a LoRA adapter -python models/LFM2-VL-450M/run.py \ - --model_path stored/lf2-450-lora/ \ +uv sync +uv run "$(dirname "$0")/../models/LFM2-VL-1.6B/run.py" \ + --model_path "$(dirname "$0")/../stored/lf2-1.6b-lora/" \ --images "https://m.media-amazon.com/images/I/71jGMgjyOOL._AC_SY300_SX300_QL70_ML2_.jpg" \ --user_prompt "Assign a category, price and weight based on the provided image. diff --git a/transformers/examples/qwen3_2b_example.sh b/transformers/examples/LFM2-VL-3B.sh old mode 100755 new mode 100644 similarity index 70% rename from transformers/examples/qwen3_2b_example.sh rename to transformers/examples/LFM2-VL-3B.sh index cfce33f..49c4024 --- a/transformers/examples/qwen3_2b_example.sh +++ b/transformers/examples/LFM2-VL-3B.sh @@ -1,8 +1,9 @@ #!/bin/bash -# Example: Run Qwen3-VL-2B-Instruct with a LoRA adapter +# Example: Run LiquidAI/LFM2-VL-3B with a LoRA adapter -python models/Qwen3-VL-2B-Instruct/run.py \ - --model_path stored/qwen3-2b-lora/ \ +uv sync +uv run "$(dirname "$0")/../models/LFM2-VL-3B/run.py" \ + --model_path "$(dirname "$0")/../stored/lf2-3b-lora/" \ --images "https://m.media-amazon.com/images/I/71jGMgjyOOL._AC_SY300_SX300_QL70_ML2_.jpg" \ --user_prompt "Assign a category, price and weight based on the provided image. diff --git a/transformers/examples/liquid_1.6b_example.sh b/transformers/examples/LFM2-VL-450M.sh old mode 100755 new mode 100644 similarity index 69% rename from transformers/examples/liquid_1.6b_example.sh rename to transformers/examples/LFM2-VL-450M.sh index ed87c72..7be8786 --- a/transformers/examples/liquid_1.6b_example.sh +++ b/transformers/examples/LFM2-VL-450M.sh @@ -1,8 +1,9 @@ #!/bin/bash -# Example: Run LiquidAI LFM2.5-VL-1.6B with a LoRA adapter +# Example: Run LiquidAI/LFM2-VL-450M with a LoRA adapter -python models/LFM2.5-VL-1.6B/run.py \ - --model_path stored/lf2-1.6b-lora/ \ +uv sync +uv run "$(dirname "$0")/../models/LFM2-VL-450M/run.py" \ + --model_path "$(dirname "$0")/../stored/lf2-450-lora/" \ --images "https://m.media-amazon.com/images/I/71jGMgjyOOL._AC_SY300_SX300_QL70_ML2_.jpg" \ --user_prompt "Assign a category, price and weight based on the provided image. diff --git a/transformers/examples/LFM2.5-VL-1.6B.sh b/transformers/examples/LFM2.5-VL-1.6B.sh new file mode 100644 index 0000000..e89d9fe --- /dev/null +++ b/transformers/examples/LFM2.5-VL-1.6B.sh @@ -0,0 +1,19 @@ +#!/bin/bash +# Example: Run LiquidAI/LFM2.5-VL-1.6B with a LoRA adapter + +uv sync +uv run "$(dirname "$0")/../models/LFM2.5-VL-1.6B/run.py" \ + --model_path "$(dirname "$0")/../stored/lf2-1.6b-lora/" \ + --images "https://m.media-amazon.com/images/I/71jGMgjyOOL._AC_SY300_SX300_QL70_ML2_.jpg" \ + --user_prompt "Assign a category, price and weight based on the provided image. + +Only return category, price (USD) and weight (pounds). + +Return output in this YAML format: +--- +Category: string +Price: float +Weight: string + +Generated output:" \ + --system_prompt "You are an expert product analyser for Amazon." diff --git a/transformers/examples/LFM2.5-VL-450M.sh b/transformers/examples/LFM2.5-VL-450M.sh new file mode 100644 index 0000000..e4d1a4b --- /dev/null +++ b/transformers/examples/LFM2.5-VL-450M.sh @@ -0,0 +1,19 @@ +#!/bin/bash +# Example: Run LiquidAI/LFM2.5-VL-450M with a LoRA adapter + +uv sync +uv run "$(dirname "$0")/../models/LFM2.5-VL-450M/run.py" \ + --model_path "$(dirname "$0")/../stored/lf2.5-450m-lora/" \ + --images "https://m.media-amazon.com/images/I/71jGMgjyOOL._AC_SY300_SX300_QL70_ML2_.jpg" \ + --user_prompt "Assign a category, price and weight based on the provided image. + +Only return category, price (USD) and weight (pounds). + +Return output in this YAML format: +--- +Category: string +Price: float +Weight: string + +Generated output:" \ + --system_prompt "You are an expert product analyser for Amazon." diff --git a/transformers/examples/Qwen3-VL-2B-Instruct.sh b/transformers/examples/Qwen3-VL-2B-Instruct.sh new file mode 100644 index 0000000..9344252 --- /dev/null +++ b/transformers/examples/Qwen3-VL-2B-Instruct.sh @@ -0,0 +1,19 @@ +#!/bin/bash +# Example: Run Qwen/Qwen3-VL-2B-Instruct with a LoRA adapter + +uv sync +uv run "$(dirname "$0")/../models/Qwen3-VL-2B-Instruct/run.py" \ + --model_path "$(dirname "$0")/../stored/qwen3-2b-lora/" \ + --images "https://m.media-amazon.com/images/I/71jGMgjyOOL._AC_SY300_SX300_QL70_ML2_.jpg" \ + --user_prompt "Assign a category, price and weight based on the provided image. + +Only return category, price (USD) and weight (pounds). + +Return output in this YAML format: +--- +Category: string +Price: float +Weight: string + +Generated output:" \ + --system_prompt "You are an expert product analyser for Amazon." diff --git a/transformers/examples/Qwen3-VL-4B-Instruct.sh b/transformers/examples/Qwen3-VL-4B-Instruct.sh new file mode 100644 index 0000000..75272b4 --- /dev/null +++ b/transformers/examples/Qwen3-VL-4B-Instruct.sh @@ -0,0 +1,19 @@ +#!/bin/bash +# Example: Run Qwen/Qwen3-VL-4B-Instruct with a LoRA adapter + +uv sync +uv run "$(dirname "$0")/../models/Qwen3-VL-4B-Instruct/run.py" \ + --model_path "$(dirname "$0")/../stored/qwen3-4b-lora/" \ + --images "https://m.media-amazon.com/images/I/71jGMgjyOOL._AC_SY300_SX300_QL70_ML2_.jpg" \ + --user_prompt "Assign a category, price and weight based on the provided image. + +Only return category, price (USD) and weight (pounds). + +Return output in this YAML format: +--- +Category: string +Price: float +Weight: string + +Generated output:" \ + --system_prompt "You are an expert product analyser for Amazon." diff --git a/transformers/examples/gemma_example.sh b/transformers/examples/gemma-3-4b-it.sh old mode 100755 new mode 100644 similarity index 70% rename from transformers/examples/gemma_example.sh rename to transformers/examples/gemma-3-4b-it.sh index 9329220..c30ad14 --- a/transformers/examples/gemma_example.sh +++ b/transformers/examples/gemma-3-4b-it.sh @@ -1,8 +1,9 @@ #!/bin/bash -# Example: Run Gemma 3 4B with a LoRA adapter +# Example: Run google/gemma-3-4b-it with a LoRA adapter -python models/gemma-3-4b-it/run.py \ - --model_path stored/gemma-lora/ \ +uv sync +uv run "$(dirname "$0")/../models/gemma-3-4b-it/run.py" \ + --model_path "$(dirname "$0")/../stored/gemma-lora/" \ --images "https://m.media-amazon.com/images/I/71jGMgjyOOL._AC_SY300_SX300_QL70_ML2_.jpg" \ --device cpu \ --user_prompt "Assign a category, price and weight based on the provided image. diff --git a/transformers/examples/gemma-3-4b-pt.sh b/transformers/examples/gemma-3-4b-pt.sh new file mode 100644 index 0000000..ca9f41d --- /dev/null +++ b/transformers/examples/gemma-3-4b-pt.sh @@ -0,0 +1,20 @@ +#!/bin/bash +# Example: Run google/gemma-3-4b-pt with a full model export + +uv sync +uv run "$(dirname "$0")/../models/gemma-3-4b-pt/run.py" \ + --model_path "$(dirname "$0")/../stored/gemma-pt/" \ + --images "https://m.media-amazon.com/images/I/71jGMgjyOOL._AC_SY300_SX300_QL70_ML2_.jpg" \ + --device cpu \ + --user_prompt "Assign a category, price and weight based on the provided image. + +Only return category, price (USD) and weight (pounds). + +Return output in this YAML format: +--- +Category: string +Price: float +Weight: string + +Generated output:" \ + --system_prompt "You are an expert product analyser for Amazon." diff --git a/transformers/examples/gemma-4-E2B-it.sh b/transformers/examples/gemma-4-E2B-it.sh new file mode 100644 index 0000000..7d7d0bf --- /dev/null +++ b/transformers/examples/gemma-4-E2B-it.sh @@ -0,0 +1,20 @@ +#!/bin/bash +# Example: Run google/gemma-4-E2B-it with a LoRA adapter + +uv sync +uv run "$(dirname "$0")/../models/gemma-4-E2B-it/run.py" \ + --model_path "$(dirname "$0")/../stored/gemma-4-e2b-lora/" \ + --images "https://m.media-amazon.com/images/I/71jGMgjyOOL._AC_SY300_SX300_QL70_ML2_.jpg" \ + --device cpu \ + --user_prompt "Assign a category, price and weight based on the provided image. + +Only return category, price (USD) and weight (pounds). + +Return output in this YAML format: +--- +Category: string +Price: float +Weight: string + +Generated output:" \ + --system_prompt "You are an expert product analyser for Amazon." diff --git a/transformers/examples/gemma_example_simple.sh b/transformers/examples/gemma_example_simple.sh deleted file mode 100755 index b425eb9..0000000 --- a/transformers/examples/gemma_example_simple.sh +++ /dev/null @@ -1,8 +0,0 @@ -#!/bin/bash -# Example: Run Gemma 3 4B with a LoRA adapter (text-only, same as test.py) - -python models/gemma-3-4b-it/run.py \ - --model_path stored/gemma-lora/ \ - --device cpu \ - --user_prompt "Quote of the day: " \ - --max_tokens 50 diff --git a/transformers/examples/qwen3_4b_example.sh b/transformers/examples/qwen3_4b_example.sh deleted file mode 100755 index 7a3d5a0..0000000 --- a/transformers/examples/qwen3_4b_example.sh +++ /dev/null @@ -1,18 +0,0 @@ -#!/bin/bash -# Example: Run Qwen3-VL-4B-Instruct with a LoRA adapter - -python models/Qwen3-VL-4B-Instruct/run.py \ - --model_path stored/qwen3-4b-lora/ \ - --images "https://m.media-amazon.com/images/I/71jGMgjyOOL._AC_SY300_SX300_QL70_ML2_.jpg" \ - --user_prompt "Assign a category, price and weight based on the provided image. - -Only return category, price (USD) and weight (pounds). - -Return output in this YAML format: ---- -Category: string -Price: float -Weight: string - -Generated output:" \ - --system_prompt "You are an expert product analyser for Amazon." diff --git a/transformers/models/LFM2-VL-1.6B/run.py b/transformers/models/LFM2-VL-1.6B/run.py new file mode 100644 index 0000000..a86b426 --- /dev/null +++ b/transformers/models/LFM2-VL-1.6B/run.py @@ -0,0 +1,56 @@ +#!/usr/bin/env python3 +"""Run inference with LiquidAI/LFM2-VL-1.6B. + +Usage: + python models/LFM2-VL-1.6B/run.py --model_path /path/to/model --images photo.jpg + python models/LFM2-VL-1.6B/run.py --model_path /path/to/model --images img.jpg --user_prompt "Classify this." --debug +""" + +import logging +import sys +from pathlib import Path + +sys.path.insert(0, str(Path(__file__).resolve().parent.parent.parent)) + +from base import ( + build_messages, + get_arg_parser, + load_images, + load_model, + print_config, + resolve_device, + resolve_dtype, + run_inference, +) + +# HuggingFace model ID — used as base model for LoRA adapters +MODEL_ID = "LiquidAI/LFM2-VL-1.6B" + +# Liquid models use image tiling with token budget control +PROCESSOR_KWARGS = { + "min_image_tokens": 64, + "max_image_tokens": 256, + "do_image_splitting": True, +} + + +def main(): + logging.basicConfig(level=logging.INFO, format="%(levelname)s %(message)s") + args = get_arg_parser(MODEL_ID).parse_args() + + device = resolve_device(args.device) + dtype = resolve_dtype(device, args.dtype, model_id=MODEL_ID) + + model, processor = load_model(MODEL_ID, args.model_path, device, dtype, processor_kwargs=PROCESSOR_KWARGS) + images = load_images(args.images, max_size=args.resize) + messages = build_messages(images, args.user_prompt, args.system_prompt) + + print_config(MODEL_ID, args.model_path, processor, images, device, dtype, args.max_tokens, args.temperature, args.resize, args.user_prompt, args.system_prompt) + + result = run_inference(model, processor, messages, images, max_tokens=args.max_tokens, temperature=args.temperature, debug=args.debug) + print("\033[31mOutput:\033[0m") + print(result) + + +if __name__ == "__main__": + main() diff --git a/transformers/models/LFM2-VL-3B/run.py b/transformers/models/LFM2-VL-3B/run.py new file mode 100644 index 0000000..b29bb57 --- /dev/null +++ b/transformers/models/LFM2-VL-3B/run.py @@ -0,0 +1,56 @@ +#!/usr/bin/env python3 +"""Run inference with LiquidAI/LFM2-VL-3B. + +Usage: + python models/LFM2-VL-3B/run.py --model_path /path/to/model --images photo.jpg + python models/LFM2-VL-3B/run.py --model_path /path/to/model --images img.jpg --user_prompt "Classify this." --debug +""" + +import logging +import sys +from pathlib import Path + +sys.path.insert(0, str(Path(__file__).resolve().parent.parent.parent)) + +from base import ( + build_messages, + get_arg_parser, + load_images, + load_model, + print_config, + resolve_device, + resolve_dtype, + run_inference, +) + +# HuggingFace model ID — used as base model for LoRA adapters +MODEL_ID = "LiquidAI/LFM2-VL-3B" + +# Liquid models use image tiling with token budget control +PROCESSOR_KWARGS = { + "min_image_tokens": 64, + "max_image_tokens": 256, + "do_image_splitting": True, +} + + +def main(): + logging.basicConfig(level=logging.INFO, format="%(levelname)s %(message)s") + args = get_arg_parser(MODEL_ID).parse_args() + + device = resolve_device(args.device) + dtype = resolve_dtype(device, args.dtype, model_id=MODEL_ID) + + model, processor = load_model(MODEL_ID, args.model_path, device, dtype, processor_kwargs=PROCESSOR_KWARGS) + images = load_images(args.images, max_size=args.resize) + messages = build_messages(images, args.user_prompt, args.system_prompt) + + print_config(MODEL_ID, args.model_path, processor, images, device, dtype, args.max_tokens, args.temperature, args.resize, args.user_prompt, args.system_prompt) + + result = run_inference(model, processor, messages, images, max_tokens=args.max_tokens, temperature=args.temperature, debug=args.debug) + print("\033[31mOutput:\033[0m") + print(result) + + +if __name__ == "__main__": + main() diff --git a/transformers/models/LFM2-VL-450M/run.py b/transformers/models/LFM2-VL-450M/run.py index 11d5b1e..61b1a73 100644 --- a/transformers/models/LFM2-VL-450M/run.py +++ b/transformers/models/LFM2-VL-450M/run.py @@ -39,7 +39,7 @@ def main(): args = get_arg_parser(MODEL_ID).parse_args() device = resolve_device(args.device) - dtype = resolve_dtype(device, args.dtype) + dtype = resolve_dtype(device, args.dtype, model_id=MODEL_ID) model, processor = load_model(MODEL_ID, args.model_path, device, dtype, processor_kwargs=PROCESSOR_KWARGS) images = load_images(args.images, max_size=args.resize) diff --git a/transformers/models/LFM2.5-VL-1.6B/run.py b/transformers/models/LFM2.5-VL-1.6B/run.py index 8c57f8e..7490623 100644 --- a/transformers/models/LFM2.5-VL-1.6B/run.py +++ b/transformers/models/LFM2.5-VL-1.6B/run.py @@ -6,11 +6,62 @@ python models/LFM2.5-VL-1.6B/run.py --model_path /path/to/model --images img.jpg --user_prompt "Classify this." --debug """ +import argparse import logging +import os +import platform import sys from pathlib import Path -sys.path.insert(0, str(Path(__file__).resolve().parent.parent.parent)) +sys.path.insert(0, str(Path(__file__).resolve().parents[2])) + +MODEL_ID = "LiquidAI/LFM2.5-VL-1.6B" + +# Liquid models use image tiling with token budget control +PROCESSOR_KWARGS = { + "min_image_tokens": 64, + "max_image_tokens": 256, + "do_image_splitting": True, +} + + +def _require_lfm25_mps_fallback() -> None: + parser = argparse.ArgumentParser(add_help=False) + parser.add_argument("--device", default="auto") + args, _ = parser.parse_known_args() + + uses_mps = args.device == "mps" + auto_on_apple_silicon = ( + args.device == "auto" + and platform.system() == "Darwin" + and platform.machine() == "arm64" + ) + if not uses_mps and not auto_on_apple_silicon: + return + + if os.environ.get("PYTORCH_ENABLE_MPS_FALLBACK") == "1": + return + + if uses_mps: + print( + "run.py: error: LiquidAI/LFM2.5-VL models on MPS require " + "PYTORCH_ENABLE_MPS_FALLBACK=1 before Python starts. " + "Re-run with `PYTORCH_ENABLE_MPS_FALLBACK=1 python ...` or choose " + "`--device cpu`/`--device cuda`.", + file=sys.stderr, + ) + raise SystemExit(2) + + print( + "run.py: error: LiquidAI/LFM2.5-VL with `--device auto` may resolve to " + "MPS on Apple Silicon and requires PYTORCH_ENABLE_MPS_FALLBACK=1 before " + "Python starts. Set the env var and re-run, or pass `--device cpu` to avoid MPS.", + file=sys.stderr, + ) + raise SystemExit(2) + + +_require_lfm25_mps_fallback() from base import ( build_messages, @@ -23,23 +74,13 @@ run_inference, ) -# HuggingFace model ID — used as base model for LoRA adapters -MODEL_ID = "LiquidAI/LFM2.5-VL-1.6B" - -# Liquid models use image tiling with token budget control -PROCESSOR_KWARGS = { - "min_image_tokens": 64, - "max_image_tokens": 256, - "do_image_splitting": True, -} - def main(): logging.basicConfig(level=logging.INFO, format="%(levelname)s %(message)s") args = get_arg_parser(MODEL_ID).parse_args() device = resolve_device(args.device) - dtype = resolve_dtype(device, args.dtype) + dtype = resolve_dtype(device, args.dtype, model_id=MODEL_ID) model, processor = load_model(MODEL_ID, args.model_path, device, dtype, processor_kwargs=PROCESSOR_KWARGS) images = load_images(args.images, max_size=args.resize) diff --git a/transformers/models/LFM2.5-VL-450M/run.py b/transformers/models/LFM2.5-VL-450M/run.py new file mode 100644 index 0000000..7eb7d54 --- /dev/null +++ b/transformers/models/LFM2.5-VL-450M/run.py @@ -0,0 +1,97 @@ +#!/usr/bin/env python3 +"""Run inference with LiquidAI/LFM2.5-VL-450M. + +Usage: + python models/LFM2.5-VL-450M/run.py --model_path /path/to/model --images photo.jpg + python models/LFM2.5-VL-450M/run.py --model_path /path/to/model --images img.jpg --user_prompt "Classify this." --debug +""" + +import argparse +import logging +import os +import platform +import sys +from pathlib import Path + +sys.path.insert(0, str(Path(__file__).resolve().parents[2])) + +MODEL_ID = "LiquidAI/LFM2.5-VL-450M" + +# Liquid models use image tiling with token budget control +PROCESSOR_KWARGS = { + "min_image_tokens": 64, + "max_image_tokens": 256, + "do_image_splitting": True, +} + + +def _require_lfm25_mps_fallback() -> None: + parser = argparse.ArgumentParser(add_help=False) + parser.add_argument("--device", default="auto") + args, _ = parser.parse_known_args() + + uses_mps = args.device == "mps" + auto_on_apple_silicon = ( + args.device == "auto" + and platform.system() == "Darwin" + and platform.machine() == "arm64" + ) + if not uses_mps and not auto_on_apple_silicon: + return + + if os.environ.get("PYTORCH_ENABLE_MPS_FALLBACK") == "1": + return + + if uses_mps: + print( + "run.py: error: LiquidAI/LFM2.5-VL models on MPS require " + "PYTORCH_ENABLE_MPS_FALLBACK=1 before Python starts. " + "Re-run with `PYTORCH_ENABLE_MPS_FALLBACK=1 python ...` or choose " + "`--device cpu`/`--device cuda`.", + file=sys.stderr, + ) + raise SystemExit(2) + + print( + "run.py: error: LiquidAI/LFM2.5-VL with `--device auto` may resolve to " + "MPS on Apple Silicon and requires PYTORCH_ENABLE_MPS_FALLBACK=1 before " + "Python starts. Set the env var and re-run, or pass `--device cpu` to avoid MPS.", + file=sys.stderr, + ) + raise SystemExit(2) + + +_require_lfm25_mps_fallback() + +from base import ( + build_messages, + get_arg_parser, + load_images, + load_model, + print_config, + resolve_device, + resolve_dtype, + run_inference, +) + + +def main(): + logging.basicConfig(level=logging.INFO, format="%(levelname)s %(message)s") + args = get_arg_parser(MODEL_ID).parse_args() + + device = resolve_device(args.device) + dtype = resolve_dtype(device, args.dtype, model_id=MODEL_ID) + + model, processor = load_model(MODEL_ID, args.model_path, device, dtype, processor_kwargs=PROCESSOR_KWARGS) + images = load_images(args.images, max_size=args.resize) + messages = build_messages(images, args.user_prompt, args.system_prompt) + + print_config(MODEL_ID, args.model_path, processor, images, device, dtype, args.max_tokens, args.temperature, args.resize, args.user_prompt, args.system_prompt) + + result = run_inference(model, processor, messages, images, max_tokens=args.max_tokens, temperature=args.temperature, debug=args.debug) + print("\033[31mOutput:\033[0m") + print(result) + + +if __name__ == "__main__": + main() diff --git a/transformers/models/Qwen3-VL-2B-Instruct/run.py b/transformers/models/Qwen3-VL-2B-Instruct/run.py index 8403684..ad7a93c 100644 --- a/transformers/models/Qwen3-VL-2B-Instruct/run.py +++ b/transformers/models/Qwen3-VL-2B-Instruct/run.py @@ -35,7 +35,7 @@ def main(): args = get_arg_parser(MODEL_ID).parse_args() device = resolve_device(args.device) - dtype = resolve_dtype(device, args.dtype) + dtype = resolve_dtype(device, args.dtype, model_id=MODEL_ID) model, processor = load_model(MODEL_ID, args.model_path, device, dtype, processor_kwargs=PROCESSOR_KWARGS) images = load_images(args.images, max_size=args.resize) diff --git a/transformers/models/Qwen3-VL-4B-Instruct/run.py b/transformers/models/Qwen3-VL-4B-Instruct/run.py index e258edb..b9368aa 100644 --- a/transformers/models/Qwen3-VL-4B-Instruct/run.py +++ b/transformers/models/Qwen3-VL-4B-Instruct/run.py @@ -12,16 +12,15 @@ sys.path.insert(0, str(Path(__file__).resolve().parent.parent.parent)) -from base import ( - build_messages, - get_arg_parser, - load_images, - load_model, - print_config, - resolve_device, - resolve_dtype, - run_inference, -) +from base import (build_messages, + get_arg_parser, + load_images, + load_model, + print_config, + resolve_device, + resolve_dtype, + run_inference, + ) # HuggingFace model ID — used as base model for LoRA adapters MODEL_ID = "Qwen/Qwen3-VL-4B-Instruct" @@ -35,7 +34,7 @@ def main(): args = get_arg_parser(MODEL_ID).parse_args() device = resolve_device(args.device) - dtype = resolve_dtype(device, args.dtype) + dtype = resolve_dtype(device, args.dtype, model_id=MODEL_ID) model, processor = load_model(MODEL_ID, args.model_path, device, dtype, processor_kwargs=PROCESSOR_KWARGS) images = load_images(args.images, max_size=args.resize) diff --git a/transformers/models/gemma-3-4b-it/run.py b/transformers/models/gemma-3-4b-it/run.py index acf11c6..066be86 100644 --- a/transformers/models/gemma-3-4b-it/run.py +++ b/transformers/models/gemma-3-4b-it/run.py @@ -37,7 +37,7 @@ def main(): args = get_arg_parser(MODEL_ID).parse_args() device = resolve_device(args.device) - dtype = resolve_dtype(device, args.dtype) + dtype = resolve_dtype(device, args.dtype, model_id=MODEL_ID) model, processor = load_model(MODEL_ID, args.model_path, device, dtype, processor_kwargs=PROCESSOR_KWARGS) images = load_images(args.images, max_size=args.resize) diff --git a/transformers/models/gemma-3-4b-pt/run.py b/transformers/models/gemma-3-4b-pt/run.py new file mode 100644 index 0000000..5755227 --- /dev/null +++ b/transformers/models/gemma-3-4b-pt/run.py @@ -0,0 +1,54 @@ +#!/usr/bin/env python3 +"""Run inference with google/gemma-3-4b-pt. + +Usage: + python models/gemma-3-4b-pt/run.py --model_path /path/to/model --images photo.jpg + python models/gemma-3-4b-pt/run.py --model_path /path/to/model --images img.jpg --user_prompt "Classify this." --debug +""" + +import logging +import sys +from pathlib import Path + +sys.path.insert(0, str(Path(__file__).resolve().parent.parent.parent)) + +from base import ( + build_messages, + get_arg_parser, + load_images, + load_model, + print_config, + resolve_device, + resolve_dtype, + run_inference, +) + +# HuggingFace model ID — used as base model for LoRA adapters +MODEL_ID = "google/gemma-3-4b-pt" + +# Gemma requires left-side padding for correct attention masking +PROCESSOR_KWARGS = { + "padding_side": "left", +} + + +def main(): + logging.basicConfig(level=logging.INFO, format="%(levelname)s %(message)s") + args = get_arg_parser(MODEL_ID).parse_args() + + device = resolve_device(args.device) + dtype = resolve_dtype(device, args.dtype, model_id=MODEL_ID) + + model, processor = load_model(MODEL_ID, args.model_path, device, dtype, processor_kwargs=PROCESSOR_KWARGS) + images = load_images(args.images, max_size=args.resize) + messages = build_messages(images, args.user_prompt, args.system_prompt) + + print_config(MODEL_ID, args.model_path, processor, images, device, dtype, args.max_tokens, args.temperature, args.resize, args.user_prompt, args.system_prompt) + + result = run_inference(model, processor, messages, images, max_tokens=args.max_tokens, temperature=args.temperature, debug=args.debug) + print("\033[31mOutput:\033[0m") + print(result) + + +if __name__ == "__main__": + main() diff --git a/transformers/models/gemma-4-E2B-it/run.py b/transformers/models/gemma-4-E2B-it/run.py new file mode 100644 index 0000000..4882c59 --- /dev/null +++ b/transformers/models/gemma-4-E2B-it/run.py @@ -0,0 +1,54 @@ +#!/usr/bin/env python3 +"""Run inference with google/gemma-4-E2B-it. + +Usage: + python models/gemma-4-E2B-it/run.py --model_path /path/to/model --images photo.jpg + python models/gemma-4-E2B-it/run.py --model_path /path/to/model --images img.jpg --user_prompt "Classify this." --debug +""" + +import logging +import sys +from pathlib import Path + +sys.path.insert(0, str(Path(__file__).resolve().parent.parent.parent)) + +from base import ( + build_messages, + get_arg_parser, + load_images, + load_model, + print_config, + resolve_device, + resolve_dtype, + run_inference, +) + +# HuggingFace model ID — used as base model for LoRA adapters +MODEL_ID = "google/gemma-4-E2B-it" + +# Gemma requires left-side padding for correct attention masking +PROCESSOR_KWARGS = { + "padding_side": "left", +} + + +def main(): + logging.basicConfig(level=logging.INFO, format="%(levelname)s %(message)s") + args = get_arg_parser(MODEL_ID).parse_args() + + device = resolve_device(args.device) + dtype = resolve_dtype(device, args.dtype, model_id=MODEL_ID) + + model, processor = load_model(MODEL_ID, args.model_path, device, dtype, processor_kwargs=PROCESSOR_KWARGS) + images = load_images(args.images, max_size=args.resize) + messages = build_messages(images, 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__pycache__/ *.pyc .venv/ +docs/ # OS .DS_Store diff --git a/README.md b/README.md index 1c9bacd..12df5cc 100644 --- a/README.md +++ b/README.md @@ -11,6 +11,7 @@ When you train a VLM on Ximilar, you can download the model and run it locally. Run your models using Python with HuggingFace Transformers and PEFT (for LoRA adapters). - Simple `run.py` script per model +- Optional helper script `transformers/scripts/download_model.py` to download a trained model artifact by UUID before inference - Supports LoRA adapters (`.safetensors`), full models (`.safetensors`), and PyTorch exports (`.pt`) - Auto-detects model format from directory contents - Works on NVIDIA GPU (CUDA), Apple Silicon (MPS), and CPU diff --git a/tests/__init__.py b/tests/__init__.py new file mode 100644 index 0000000..8c14823 --- /dev/null +++ b/tests/__init__.py @@ -0,0 +1 @@ +# Test package for local example helpers. diff --git a/transformers/README.md b/transformers/README.md index 93568a3..ac7313d 100644 --- a/transformers/README.md +++ b/transformers/README.md @@ -90,6 +90,21 @@ cd transformers source .venv/bin/activate ``` +### Download a model by UUID + +If you want to fetch a trained model artifact directly from the Ximilar backend first, use the helper script: + +```bash +export XIMILAR_API_TOKEN=your_api_token +export XIMILAR_API_URL=https://api.ximilar.com/vlm/v2 + +uv run python scripts/download_model.py \ + --model_uuid 00000000-0000-0000-0000-000000000000 \ + --output_path /path/to/local/model +``` + +Then run any of the existing example scripts with `--model_path /path/to/local/model`. + ### Basic usage ```bash diff --git a/transformers/client.py b/transformers/client.py new file mode 100644 index 0000000..12caba0 --- /dev/null +++ b/transformers/client.py @@ -0,0 +1,111 @@ +"""Helpers for downloading trained model artifacts from the Ximilar backend.""" + +from __future__ import annotations + +import json +import os +import shutil +import tarfile +import tempfile +import urllib.error +import urllib.parse +import urllib.request +import zipfile +from pathlib import Path + + +VALID_MARKERS = ("adapter_config.json", "model.pt", "config.json") + + +def get_required_env(name: str) -> str: + value = os.environ.get(name) + if not value: + raise RuntimeError(f"Missing required environment variable: {name}") + return value + + +def request_model_download(model_uuid: str, api_url: str, api_token: str) -> dict: + request = urllib.request.Request( + f"{api_url.rstrip('/')}/model/{model_uuid}/request-download", + headers={"Authorization": f"Token {api_token}"}, + method="GET", + ) + try: + with urllib.request.urlopen(request) as response: + payload = json.loads(response.read().decode("utf-8")) + except urllib.error.HTTPError as exc: + body = exc.read().decode("utf-8", errors="replace")[:500] + raise RuntimeError(f"Backend request failed with HTTP {exc.code}: {body}") from exc + except urllib.error.URLError as exc: + raise RuntimeError(f"Backend request failed: {exc.reason}") from exc + + if "download_url" not in payload: + raise RuntimeError("Backend response is missing download_url") + return payload + + +def download_file(url: str, destination: Path) -> Path: + destination.parent.mkdir(parents=True, exist_ok=True) + try: + with urllib.request.urlopen(url) as response, destination.open("wb") as output: + shutil.copyfileobj(response, output) + except urllib.error.HTTPError as exc: + body = exc.read().decode("utf-8", errors="replace")[:500] + raise RuntimeError(f"Artifact download failed with HTTP {exc.code}: {body}") from exc + except urllib.error.URLError as exc: + raise RuntimeError(f"Artifact download failed: {exc.reason}") from exc + return destination + + +def extract_artifact(archive_path: Path, output_path: Path) -> Path: + if output_path.exists(): + shutil.rmtree(output_path) + output_path.mkdir(parents=True, exist_ok=True) + + suffixes = archive_path.suffixes + if archive_path.suffix == ".zip": + with zipfile.ZipFile(archive_path) as zf: + zf.extractall(output_path) + elif suffixes[-2:] == [".tar", ".gz"] or archive_path.suffix in {".tgz", ".tar"}: + with tarfile.open(archive_path, "r:*") as tf: + tf.extractall(output_path, filter="data") + else: + raise RuntimeError(f"Unsupported artifact type: {archive_path.name}") + return output_path + + +def resolve_model_dir(path: Path) -> Path: + if any((path / marker).exists() for marker in VALID_MARKERS): + return path + + child_dirs = [child for child in path.iterdir() if child.is_dir()] + if len(child_dirs) == 1 and any((child_dirs[0] / marker).exists() for marker in VALID_MARKERS): + return child_dirs[0] + + return path + + +def validate_model_dir(path: Path) -> None: + resolved = resolve_model_dir(path) + if any((resolved / marker).exists() for marker in VALID_MARKERS): + return + markers = ", ".join(VALID_MARKERS) + raise RuntimeError(f"Extracted directory does not look like a model directory. Expected one of: {markers}") + + +def download_and_extract_model(model_uuid: str, output_path: Path, api_url: str, api_token: str) -> Path: + payload = request_model_download(model_uuid=model_uuid, api_url=api_url, api_token=api_token) + download_url = payload["download_url"] + + staging_dir = Path(tempfile.gettempdir()) / "ximilar-vlm-downloads" / model_uuid + staging_dir.mkdir(parents=True, exist_ok=True) + + parsed_url = urllib.parse.urlparse(download_url) + filename = Path(parsed_url.path).name or "artifact.bin" + archive_path = staging_dir / filename + download_file(download_url, archive_path) + + extracted_root = extract_artifact(archive_path, output_path) + model_dir = resolve_model_dir(extracted_root) + validate_model_dir(model_dir) + return model_dir diff --git a/transformers/scripts/download_model.py b/transformers/scripts/download_model.py new file mode 100644 index 0000000..0aa0e6a --- /dev/null +++ b/transformers/scripts/download_model.py @@ -0,0 +1,35 @@ +#!/usr/bin/env python3 +"""Download a trained Ximilar VLM model artifact by UUID.""" + +import argparse +import sys +from pathlib import Path + +sys.path.insert(0, str(Path(__file__).resolve().parent.parent)) + +from client import download_and_extract_model, get_required_env + + +def get_arg_parser() -> argparse.ArgumentParser: + parser = argparse.ArgumentParser(description="Download a trained Ximilar VLM model by UUID.") + parser.add_argument("--model_uuid", required=True, help="UUID of the trained VLM model") + parser.add_argument("--output_path", required=True, help="Directory where the model should be extracted") + return parser + + +def main() -> None: + args = get_arg_parser().parse_args() + api_token = get_required_env("XIMILAR_API_TOKEN") + api_url = get_required_env("XIMILAR_API_URL") + output_path = Path(args.output_path).expanduser().resolve() + result = download_and_extract_model( + model_uuid=args.model_uuid, + output_path=output_path, + api_url=api_url, + api_token=api_token, + ) + print(result) + + +if __name__ == "__main__": + main() From 2650746425e02243411880b796fe64baeafe9097 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Zden=C4=9Bk=20Lape=C5=A1?= Date: Mon, 27 Apr 2026 16:23:22 +0000 Subject: [PATCH 3/6] new transformer models --- .gitignore | 3 ++ .../.python-version | 0 transformers/README.md | 42 +++++++------------ transformers/client.py | 14 ++++++- transformers/examples/LFM2-VL-1.6B.sh | 4 +- transformers/examples/LFM2-VL-3B.sh | 0 transformers/examples/LFM2-VL-450M.sh | 0 transformers/examples/LFM2.5-VL-1.6B.sh | 0 transformers/examples/LFM2.5-VL-450M.sh | 4 +- transformers/examples/Qwen3-VL-2B-Instruct.sh | 0 transformers/examples/Qwen3-VL-4B-Instruct.sh | 0 transformers/examples/gemma-3-4b-it.sh | 0 transformers/examples/gemma-3-4b-pt.sh | 0 transformers/examples/gemma-4-E2B-it.sh | 5 +-- pyproject.toml => transformers/pyproject.toml | 0 transformers/scripts/download_model.py | 4 +- uv.lock => transformers/uv.lock | 0 17 files changed, 39 insertions(+), 37 deletions(-) rename .python-version => transformers/.python-version (100%) mode change 100644 => 100755 transformers/examples/LFM2-VL-1.6B.sh mode change 100644 => 100755 transformers/examples/LFM2-VL-3B.sh mode change 100644 => 100755 transformers/examples/LFM2-VL-450M.sh mode change 100644 => 100755 transformers/examples/LFM2.5-VL-1.6B.sh mode change 100644 => 100755 transformers/examples/LFM2.5-VL-450M.sh mode change 100644 => 100755 transformers/examples/Qwen3-VL-2B-Instruct.sh mode change 100644 => 100755 transformers/examples/Qwen3-VL-4B-Instruct.sh mode change 100644 => 100755 transformers/examples/gemma-3-4b-it.sh mode change 100644 => 100755 transformers/examples/gemma-3-4b-pt.sh mode change 100644 => 100755 transformers/examples/gemma-4-E2B-it.sh rename pyproject.toml => transformers/pyproject.toml (100%) rename uv.lock => transformers/uv.lock (100%) diff --git a/.gitignore b/.gitignore index 6452bfd..b336278 100644 --- a/.gitignore +++ b/.gitignore @@ -15,3 +15,6 @@ docs/ .DS_Store .env .idea/ +.codex + +tmp/ diff --git a/.python-version b/transformers/.python-version similarity index 100% rename from .python-version rename to transformers/.python-version diff --git a/transformers/README.md b/transformers/README.md index ac7313d..a8f8bf6 100644 --- a/transformers/README.md +++ b/transformers/README.md @@ -43,26 +43,14 @@ The scripts auto-detect the format from the model directory and handle all three ## Setup +From the repository root: + ```bash # Install uv (fast Python package manager) curl -LsSf https://astral.sh/uv/install.sh | sh -# Create virtual environment -uv venv .venv --python 3.12 -source .venv/bin/activate - -# Install dependencies -uv pip install "transformers>=5.1.0" "peft>=0.18.1" "accelerate>=1.12.0" "safetensors>=0.7.0" pillow -``` - -Then install PyTorch for your platform: - -```bash -# Linux with NVIDIA GPU (CUDA 12.8, but you can try to specify yours version) -uv pip install torch torchvision --index-url https://download.pytorch.org/whl/cu128 - -# macOS (Apple Silicon / CPU) or Linux CPU-only -uv pip install torch torchvision +# Create/update the virtual environment and install dependencies from pyproject.toml +uv sync ``` ### HuggingFace authentication (required for some models) @@ -77,33 +65,33 @@ Some base models (e.g. **google/gemma-3-4b-it**) are gated — you must accept t export HF_TOKEN=hf_your_token_here ``` -To make it permanent, add the line to your `~/.bashrc` or `~/.zshrc`. - -Without this, gated models will fail with `OSError: ... does not appear to have a file named model.safetensors`. ## Usage -All commands below assume you are inside the `transformers/` directory: +Install dependencies first: ```bash -cd transformers -source .venv/bin/activate +uv sync ``` ### Download a model by UUID -If you want to fetch a trained model artifact directly from the Ximilar backend first, use the helper script: +If you want to fetch a trained model artifact directly from the Ximilar backend first, run the helper script from the repository root: ```bash export XIMILAR_API_TOKEN=your_api_token export XIMILAR_API_URL=https://api.ximilar.com/vlm/v2 -uv run python scripts/download_model.py \ - --model_uuid 00000000-0000-0000-0000-000000000000 \ - --output_path /path/to/local/model +uv run transformers/scripts/download_model.py \ + --model-uuid 00000000-0000-0000-0000-000000000000 \ + --output-path /path/to/local/model ``` -Then run any of the existing example scripts with `--model_path /path/to/local/model`. +Then switch into the `transformers/` directory and run any of the existing example scripts with `--model_path /path/to/local/model`: + +```bash +cd transformers +``` ### Basic usage diff --git a/transformers/client.py b/transformers/client.py index 12caba0..7d0134d 100644 --- a/transformers/client.py +++ b/transformers/client.py @@ -15,6 +15,7 @@ VALID_MARKERS = ("adapter_config.json", "model.pt", "config.json") +DEFAULT_VLM_API_PATH = "/vlm/v2" def get_required_env(name: str) -> str: @@ -24,9 +25,20 @@ def get_required_env(name: str) -> str: return value +def normalize_vlm_api_url(api_url: str) -> str: + parsed = urllib.parse.urlsplit(api_url) + path = parsed.path.rstrip("/") + if not path: + path = DEFAULT_VLM_API_PATH + elif path == "/vlm": + path = DEFAULT_VLM_API_PATH + return urllib.parse.urlunsplit((parsed.scheme, parsed.netloc, path, parsed.query, parsed.fragment)) + + def request_model_download(model_uuid: str, api_url: str, api_token: str) -> dict: + base_api_url = normalize_vlm_api_url(api_url) request = urllib.request.Request( - f"{api_url.rstrip('/')}/model/{model_uuid}/request-download", + f"{base_api_url}/model/{model_uuid}/request-download/", headers={"Authorization": f"Token {api_token}"}, method="GET", ) diff --git a/transformers/examples/LFM2-VL-1.6B.sh b/transformers/examples/LFM2-VL-1.6B.sh old mode 100644 new mode 100755 index bcd2cc8..d04d821 --- a/transformers/examples/LFM2-VL-1.6B.sh +++ b/transformers/examples/LFM2-VL-1.6B.sh @@ -2,8 +2,8 @@ # Example: Run LiquidAI/LFM2-VL-1.6B with a LoRA adapter uv sync -uv run "$(dirname "$0")/../models/LFM2-VL-1.6B/run.py" \ - --model_path "$(dirname "$0")/../stored/lf2-1.6b-lora/" \ +uv run transformers/models/LFM2-VL-1.6B/run.py \ + --model_path tmp/923a29bb-cf33-4400-b06d-2948a90e5a59/model/ \ --images "https://m.media-amazon.com/images/I/71jGMgjyOOL._AC_SY300_SX300_QL70_ML2_.jpg" \ --user_prompt "Assign a category, price and weight based on the provided image. diff --git a/transformers/examples/LFM2-VL-3B.sh b/transformers/examples/LFM2-VL-3B.sh old mode 100644 new mode 100755 diff --git a/transformers/examples/LFM2-VL-450M.sh b/transformers/examples/LFM2-VL-450M.sh old mode 100644 new mode 100755 diff --git a/transformers/examples/LFM2.5-VL-1.6B.sh b/transformers/examples/LFM2.5-VL-1.6B.sh old mode 100644 new mode 100755 diff --git a/transformers/examples/LFM2.5-VL-450M.sh b/transformers/examples/LFM2.5-VL-450M.sh old mode 100644 new mode 100755 index e4d1a4b..d8aee55 --- a/transformers/examples/LFM2.5-VL-450M.sh +++ b/transformers/examples/LFM2.5-VL-450M.sh @@ -2,8 +2,8 @@ # Example: Run LiquidAI/LFM2.5-VL-450M with a LoRA adapter uv sync -uv run "$(dirname "$0")/../models/LFM2.5-VL-450M/run.py" \ - --model_path "$(dirname "$0")/../stored/lf2.5-450m-lora/" \ +uv run transformers/models/LFM2.5-VL-450M/run.py \ + --model_path tmp/a22afc30-0a92-4d86-ac7a-ec31be04c5e1/model/ \ --images "https://m.media-amazon.com/images/I/71jGMgjyOOL._AC_SY300_SX300_QL70_ML2_.jpg" \ --user_prompt "Assign a category, price and weight based on the provided image. diff --git a/transformers/examples/Qwen3-VL-2B-Instruct.sh b/transformers/examples/Qwen3-VL-2B-Instruct.sh old mode 100644 new mode 100755 diff --git a/transformers/examples/Qwen3-VL-4B-Instruct.sh b/transformers/examples/Qwen3-VL-4B-Instruct.sh old mode 100644 new mode 100755 diff --git a/transformers/examples/gemma-3-4b-it.sh b/transformers/examples/gemma-3-4b-it.sh old mode 100644 new mode 100755 diff --git a/transformers/examples/gemma-3-4b-pt.sh b/transformers/examples/gemma-3-4b-pt.sh old mode 100644 new mode 100755 diff --git a/transformers/examples/gemma-4-E2B-it.sh b/transformers/examples/gemma-4-E2B-it.sh old mode 100644 new mode 100755 index 7d7d0bf..02d0883 --- a/transformers/examples/gemma-4-E2B-it.sh +++ b/transformers/examples/gemma-4-E2B-it.sh @@ -2,10 +2,9 @@ # Example: Run google/gemma-4-E2B-it with a LoRA adapter uv sync -uv run "$(dirname "$0")/../models/gemma-4-E2B-it/run.py" \ - --model_path "$(dirname "$0")/../stored/gemma-4-e2b-lora/" \ +uv run transformers/models/gemma-4-E2B-it/run.py \ + --model_path tmp/ef34953d-6799-489a-89a8-39509d4db21e/model/ \ --images "https://m.media-amazon.com/images/I/71jGMgjyOOL._AC_SY300_SX300_QL70_ML2_.jpg" \ - --device cpu \ --user_prompt "Assign a category, price and weight based on the provided image. Only return category, price (USD) and weight (pounds). diff --git a/pyproject.toml b/transformers/pyproject.toml similarity index 100% rename from pyproject.toml rename to transformers/pyproject.toml diff --git a/transformers/scripts/download_model.py b/transformers/scripts/download_model.py index 0aa0e6a..718df75 100644 --- a/transformers/scripts/download_model.py +++ b/transformers/scripts/download_model.py @@ -12,8 +12,8 @@ def get_arg_parser() -> argparse.ArgumentParser: parser = argparse.ArgumentParser(description="Download a trained Ximilar VLM model by UUID.") - parser.add_argument("--model_uuid", required=True, help="UUID of the trained VLM model") - parser.add_argument("--output_path", required=True, help="Directory where the model should be extracted") + parser.add_argument("--model-uuid", required=True, help="UUID of the trained VLM model") + parser.add_argument("--output-path", required=True, help="Directory where the model should be extracted") return parser diff --git a/uv.lock b/transformers/uv.lock similarity index 100% rename from uv.lock rename to transformers/uv.lock From a8f5e69def82af35234da3a0611b5e115211f936 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Zden=C4=9Bk=20Lape=C5=A1?= Date: Wed, 29 Apr 2026 17:04:10 +0000 Subject: [PATCH 4/6] download script --- scripts/download-model.sh | 9 +++++++++ 1 file changed, 9 insertions(+) create mode 100644 scripts/download-model.sh diff --git a/scripts/download-model.sh b/scripts/download-model.sh new file mode 100644 index 0000000..19bf184 --- /dev/null +++ b/scripts/download-model.sh @@ -0,0 +1,9 @@ + +export MODEL_URL="" +export FOLDER_PATH="tmp/models/conversion_936c3bb7-e055-4dd8-a0a3-6fc2bcfe036d" +wget \ + --output-document "$FOLDER_PATH".zip + "$MODEL_URL" +unzip -o "$FOLDER_PATH".zip -d $FOLDER_PATH +ls -la "$FOLDER_PATH" +rm "$FOLDER_PATH".zip From c4ead56ebe034d24334fca9de2c2c1a4d04fa18b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Zden=C4=9Bk=20Lape=C5=A1?= Date: Thu, 30 Apr 2026 14:31:16 +0000 Subject: [PATCH 5/6] download loggin --- transformers/scripts/download_model.py | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/transformers/scripts/download_model.py b/transformers/scripts/download_model.py index 718df75..bf2f4ad 100644 --- a/transformers/scripts/download_model.py +++ b/transformers/scripts/download_model.py @@ -19,15 +19,20 @@ def get_arg_parser() -> argparse.ArgumentParser: def main() -> None: args = get_arg_parser().parse_args() + print(f"[DEBUG] Parsed arguments: model_uuid={args.model_uuid} output_path={args.output_path}", file=sys.stderr) api_token = get_required_env("XIMILAR_API_TOKEN") api_url = get_required_env("XIMILAR_API_URL") + print(f"[DEBUG] Loaded API configuration: api_url={api_url}", file=sys.stderr) output_path = Path(args.output_path).expanduser().resolve() + print(f"[DEBUG] Resolved output path: {output_path}", file=sys.stderr) + print(f"[DEBUG] Starting model download for {args.model_uuid}", file=sys.stderr) result = download_and_extract_model( model_uuid=args.model_uuid, output_path=output_path, api_url=api_url, api_token=api_token, ) + print(f"[DEBUG] Model download finished: {result}", file=sys.stderr) print(result) From 718c1f6e74f6c662cc06ac574f75c3d1dd1cfc32 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Zden=C4=9Bk=20Lape=C5=A1?= Date: Thu, 30 Apr 2026 16:04:06 +0000 Subject: [PATCH 6/6] Updated run.py + example/*.sh + added logign to download_model script --- transformers/examples/LFM2-VL-1.6B.sh | 10 ++++++++-- transformers/examples/LFM2-VL-3B.sh | 10 ++++++++-- transformers/examples/LFM2-VL-450M.sh | 10 ++++++++-- transformers/examples/LFM2.5-VL-1.6B.sh | 10 ++++++++-- transformers/examples/LFM2.5-VL-450M.sh | 10 ++++++++-- transformers/examples/Qwen3-VL-2B-Instruct.sh | 10 ++++++++-- transformers/examples/Qwen3-VL-4B-Instruct.sh | 10 ++++++++-- transformers/examples/gemma-3-4b-it.sh | 10 ++++++++-- transformers/examples/gemma-3-4b-pt.sh | 10 ++++++++-- transformers/examples/gemma-4-E2B-it.sh | 10 ++++++++-- transformers/models/LFM2-VL-1.6B/run.py | 2 -- transformers/models/LFM2-VL-3B/run.py | 2 -- transformers/models/LFM2-VL-450M/run.py | 2 -- transformers/models/Qwen3-VL-2B-Instruct/run.py | 2 -- transformers/models/Qwen3-VL-4B-Instruct/run.py | 2 -- transformers/models/gemma-3-4b-it/run.py | 2 -- transformers/models/gemma-3-4b-pt/run.py | 2 -- transformers/models/gemma-4-E2B-it/run.py | 2 -- transformers/scripts/download_model.py | 6 +++++- 19 files changed, 85 insertions(+), 37 deletions(-) diff --git a/transformers/examples/LFM2-VL-1.6B.sh b/transformers/examples/LFM2-VL-1.6B.sh index d04d821..c069c0f 100755 --- a/transformers/examples/LFM2-VL-1.6B.sh +++ b/transformers/examples/LFM2-VL-1.6B.sh @@ -2,8 +2,14 @@ # Example: Run LiquidAI/LFM2-VL-1.6B with a LoRA adapter uv sync -uv run transformers/models/LFM2-VL-1.6B/run.py \ - --model_path tmp/923a29bb-cf33-4400-b06d-2948a90e5a59/model/ \ +export MODEL_PATH="../stored/lf2-1.6b-lora/model" +export RUN_SCRIPT="./models/LFM2-VL-1.6B/run.py" +[ -d "$MODEL_PATH" ] && [ -f "$RUN_SCRIPT" ] || echo "INVALID PATHS" +[ -d "$MODEL_PATH" ] && [ -f "$RUN_SCRIPT" ] && [[ "$(basename "$PWD")" == "transformers" ]] || echo "You have to be in the transformers directory to run this script" +echo "Using model path: $MODEL_PATH" +echo "Using run script: $RUN_SCRIPT" +uv run $RUN_SCRIPT \ + --model_path "$MODEL_PATH" \ --images "https://m.media-amazon.com/images/I/71jGMgjyOOL._AC_SY300_SX300_QL70_ML2_.jpg" \ --user_prompt "Assign a category, price and weight based on the provided image. diff --git a/transformers/examples/LFM2-VL-3B.sh b/transformers/examples/LFM2-VL-3B.sh index 49c4024..fdf05ee 100755 --- a/transformers/examples/LFM2-VL-3B.sh +++ b/transformers/examples/LFM2-VL-3B.sh @@ -2,8 +2,14 @@ # Example: Run LiquidAI/LFM2-VL-3B with a LoRA adapter uv sync -uv run "$(dirname "$0")/../models/LFM2-VL-3B/run.py" \ - --model_path "$(dirname "$0")/../stored/lf2-3b-lora/" \ +export MODEL_PATH="../stored/lf2-3b-lora/model" +export RUN_SCRIPT="./models/LFM2-VL-3B/run.py" +[ -d "$MODEL_PATH" ] && [ -f "$RUN_SCRIPT" ] || echo "INVALID PATHS" +[ -d "$MODEL_PATH" ] && [ -f "$RUN_SCRIPT" ] && [[ "$(basename "$PWD")" == "transformers" ]] || echo "You have to be in the transformers directory to run this script" +echo "Using model path: $MODEL_PATH" +echo "Using run script: $RUN_SCRIPT" +uv run $RUN_SCRIPT \ + --model_path "$MODEL_PATH" \ --images "https://m.media-amazon.com/images/I/71jGMgjyOOL._AC_SY300_SX300_QL70_ML2_.jpg" \ --user_prompt "Assign a category, price and weight based on the provided image. diff --git a/transformers/examples/LFM2-VL-450M.sh b/transformers/examples/LFM2-VL-450M.sh index 7be8786..9aae046 100755 --- a/transformers/examples/LFM2-VL-450M.sh +++ b/transformers/examples/LFM2-VL-450M.sh @@ -2,8 +2,14 @@ # Example: Run LiquidAI/LFM2-VL-450M with a LoRA adapter uv sync -uv run "$(dirname "$0")/../models/LFM2-VL-450M/run.py" \ - --model_path "$(dirname "$0")/../stored/lf2-450-lora/" \ +export MODEL_PATH="../stored/lf2-450-lora/model" +export RUN_SCRIPT="./models/LFM2-VL-450M/run.py" +[ -d "$MODEL_PATH" ] && [ -f "$RUN_SCRIPT" ] || echo "INVALID PATHS" +[ -d "$MODEL_PATH" ] && [ -f "$RUN_SCRIPT" ] && [[ "$(basename "$PWD")" == "transformers" ]] || echo "You have to be in the transformers directory to run this script" +echo "Using model path: $MODEL_PATH" +echo "Using run script: $RUN_SCRIPT" +uv run $RUN_SCRIPT \ + --model_path "$MODEL_PATH" \ --images "https://m.media-amazon.com/images/I/71jGMgjyOOL._AC_SY300_SX300_QL70_ML2_.jpg" \ --user_prompt "Assign a category, price and weight based on the provided image. diff --git a/transformers/examples/LFM2.5-VL-1.6B.sh b/transformers/examples/LFM2.5-VL-1.6B.sh index e89d9fe..b089abb 100755 --- a/transformers/examples/LFM2.5-VL-1.6B.sh +++ b/transformers/examples/LFM2.5-VL-1.6B.sh @@ -2,8 +2,14 @@ # Example: Run LiquidAI/LFM2.5-VL-1.6B with a LoRA adapter uv sync -uv run "$(dirname "$0")/../models/LFM2.5-VL-1.6B/run.py" \ - --model_path "$(dirname "$0")/../stored/lf2-1.6b-lora/" \ +export MODEL_PATH="../stored/lfm2.5-1.6b-lora/model" +export RUN_SCRIPT="./models/LFM2.5-VL-1.6B/run.py" +[ -d "$MODEL_PATH" ] && [ -f "$RUN_SCRIPT" ] || echo "INVALID PATHS" +[ -d "$MODEL_PATH" ] && [ -f "$RUN_SCRIPT" ] && [[ "$(basename "$PWD")" == "transformers" ]] || echo "You have to be in the transformers directory to run this script" +echo "Using model path: $MODEL_PATH" +echo "Using run script: $RUN_SCRIPT" +uv run $RUN_SCRIPT \ + --model_path "$MODEL_PATH" \ --images "https://m.media-amazon.com/images/I/71jGMgjyOOL._AC_SY300_SX300_QL70_ML2_.jpg" \ --user_prompt "Assign a category, price and weight based on the provided image. diff --git a/transformers/examples/LFM2.5-VL-450M.sh b/transformers/examples/LFM2.5-VL-450M.sh index d8aee55..f7fd52b 100755 --- a/transformers/examples/LFM2.5-VL-450M.sh +++ b/transformers/examples/LFM2.5-VL-450M.sh @@ -2,8 +2,14 @@ # Example: Run LiquidAI/LFM2.5-VL-450M with a LoRA adapter uv sync -uv run transformers/models/LFM2.5-VL-450M/run.py \ - --model_path tmp/a22afc30-0a92-4d86-ac7a-ec31be04c5e1/model/ \ +export MODEL_PATH="../stored/lfm2.5-450m-lora/model" +export RUN_SCRIPT="./models/LFM2.5-VL-450M/run.py" +[ -d "$MODEL_PATH" ] && [ -f "$RUN_SCRIPT" ] || echo "INVALID PATHS" +[ -d "$MODEL_PATH" ] && [ -f "$RUN_SCRIPT" ] && [[ "$(basename "$PWD")" == "transformers" ]] || echo "You have to be in the transformers directory to run this script" +echo "Using model path: $MODEL_PATH" +echo "Using run script: $RUN_SCRIPT" +uv run $RUN_SCRIPT \ + --model_path "$MODEL_PATH" \ --images "https://m.media-amazon.com/images/I/71jGMgjyOOL._AC_SY300_SX300_QL70_ML2_.jpg" \ --user_prompt "Assign a category, price and weight based on the provided image. diff --git a/transformers/examples/Qwen3-VL-2B-Instruct.sh b/transformers/examples/Qwen3-VL-2B-Instruct.sh index 9344252..2afc114 100755 --- a/transformers/examples/Qwen3-VL-2B-Instruct.sh +++ b/transformers/examples/Qwen3-VL-2B-Instruct.sh @@ -2,8 +2,14 @@ # Example: Run Qwen/Qwen3-VL-2B-Instruct with a LoRA adapter uv sync -uv run "$(dirname "$0")/../models/Qwen3-VL-2B-Instruct/run.py" \ - --model_path "$(dirname "$0")/../stored/qwen3-2b-lora/" \ +export MODEL_PATH="../stored/qwen3-2b-lora/model" +export RUN_SCRIPT="./models/Qwen3-VL-2B-Instruct/run.py" +[ -d "$MODEL_PATH" ] && [ -f "$RUN_SCRIPT" ] || echo "INVALID PATHS" +[ -d "$MODEL_PATH" ] && [ -f "$RUN_SCRIPT" ] && [[ "$(basename "$PWD")" == "transformers" ]] || echo "You have to be in the transformers directory to run this script" +echo "Using model path: $MODEL_PATH" +echo "Using run script: $RUN_SCRIPT" +uv run $RUN_SCRIPT \ + --model_path "$MODEL_PATH" \ --images "https://m.media-amazon.com/images/I/71jGMgjyOOL._AC_SY300_SX300_QL70_ML2_.jpg" \ --user_prompt "Assign a category, price and weight based on the provided image. diff --git a/transformers/examples/Qwen3-VL-4B-Instruct.sh b/transformers/examples/Qwen3-VL-4B-Instruct.sh index 75272b4..e69d3d2 100755 --- a/transformers/examples/Qwen3-VL-4B-Instruct.sh +++ b/transformers/examples/Qwen3-VL-4B-Instruct.sh @@ -2,8 +2,14 @@ # Example: Run Qwen/Qwen3-VL-4B-Instruct with a LoRA adapter uv sync -uv run "$(dirname "$0")/../models/Qwen3-VL-4B-Instruct/run.py" \ - --model_path "$(dirname "$0")/../stored/qwen3-4b-lora/" \ +export MODEL_PATH="../stored/qwen3-4b-lora/model" +export RUN_SCRIPT="./models/Qwen3-VL-4B-Instruct/run.py" +[ -d "$MODEL_PATH" ] && [ -f "$RUN_SCRIPT" ] || echo "INVALID PATHS" +[ -d "$MODEL_PATH" ] && [ -f "$RUN_SCRIPT" ] && [[ "$(basename "$PWD")" == "transformers" ]] || echo "You have to be in the transformers directory to run this script" +echo "Using model path: $MODEL_PATH" +echo "Using run script: $RUN_SCRIPT" +uv run $RUN_SCRIPT \ + --model_path "$MODEL_PATH" \ --images "https://m.media-amazon.com/images/I/71jGMgjyOOL._AC_SY300_SX300_QL70_ML2_.jpg" \ --user_prompt "Assign a category, price and weight based on the provided image. diff --git a/transformers/examples/gemma-3-4b-it.sh b/transformers/examples/gemma-3-4b-it.sh index c30ad14..40747ac 100755 --- a/transformers/examples/gemma-3-4b-it.sh +++ b/transformers/examples/gemma-3-4b-it.sh @@ -2,8 +2,14 @@ # Example: Run google/gemma-3-4b-it with a LoRA adapter uv sync -uv run "$(dirname "$0")/../models/gemma-3-4b-it/run.py" \ - --model_path "$(dirname "$0")/../stored/gemma-lora/" \ +export MODEL_PATH="../stored/gemma-lora/model" +export RUN_SCRIPT="./models/gemma-3-4b-it/run.py" +[ -d "$MODEL_PATH" ] && [ -f "$RUN_SCRIPT" ] || echo "INVALID PATHS" +[ -d "$MODEL_PATH" ] && [ -f "$RUN_SCRIPT" ] && [[ "$(basename "$PWD")" == "transformers" ]] || echo "You have to be in the transformers directory to run this script" +echo "Using model path: $MODEL_PATH" +echo "Using run script: $RUN_SCRIPT" +uv run $RUN_SCRIPT \ + --model_path "$MODEL_PATH" \ --images "https://m.media-amazon.com/images/I/71jGMgjyOOL._AC_SY300_SX300_QL70_ML2_.jpg" \ --device cpu \ --user_prompt "Assign a category, price and weight based on the provided image. diff --git a/transformers/examples/gemma-3-4b-pt.sh b/transformers/examples/gemma-3-4b-pt.sh index ca9f41d..a95cdf9 100755 --- a/transformers/examples/gemma-3-4b-pt.sh +++ b/transformers/examples/gemma-3-4b-pt.sh @@ -2,8 +2,14 @@ # Example: Run google/gemma-3-4b-pt with a full model export uv sync -uv run "$(dirname "$0")/../models/gemma-3-4b-pt/run.py" \ - --model_path "$(dirname "$0")/../stored/gemma-pt/" \ +export MODEL_PATH="../stored/gemma-pt/model" +export RUN_SCRIPT="./models/gemma-3-4b-pt/run.py" +[ -d "$MODEL_PATH" ] && [ -f "$RUN_SCRIPT" ] || echo "INVALID PATHS" +[ -d "$MODEL_PATH" ] && [ -f "$RUN_SCRIPT" ] && [[ "$(basename "$PWD")" == "transformers" ]] || echo "You have to be in the transformers directory to run this script" +echo "Using model path: $MODEL_PATH" +echo "Using run script: $RUN_SCRIPT" +uv run $RUN_SCRIPT \ + --model_path "$MODEL_PATH" \ --images "https://m.media-amazon.com/images/I/71jGMgjyOOL._AC_SY300_SX300_QL70_ML2_.jpg" \ --device cpu \ --user_prompt "Assign a category, price and weight based on the provided image. diff --git a/transformers/examples/gemma-4-E2B-it.sh b/transformers/examples/gemma-4-E2B-it.sh index 02d0883..d1b82f7 100755 --- a/transformers/examples/gemma-4-E2B-it.sh +++ b/transformers/examples/gemma-4-E2B-it.sh @@ -2,8 +2,14 @@ # Example: Run google/gemma-4-E2B-it with a LoRA adapter uv sync -uv run transformers/models/gemma-4-E2B-it/run.py \ - --model_path tmp/ef34953d-6799-489a-89a8-39509d4db21e/model/ \ +export MODEL_PATH="../stored/gemma-4-e2b-lora/model" +export RUN_SCRIPT="./models/gemma-4-E2B-it/run.py" +[ -d "$MODEL_PATH" ] && [ -f "$RUN_SCRIPT" ] || echo "INVALID PATHS" +[ -d "$MODEL_PATH" ] && [ -f "$RUN_SCRIPT" ] && [[ "$(basename "$PWD")" == "transformers" ]] || echo "You have to be in the transformers directory to run this script" +echo "Using model path: $MODEL_PATH" +echo "Using run script: $RUN_SCRIPT" +uv run $RUN_SCRIPT \ + --model_path "$MODEL_PATH" \ --images "https://m.media-amazon.com/images/I/71jGMgjyOOL._AC_SY300_SX300_QL70_ML2_.jpg" \ --user_prompt "Assign a category, price and weight based on the provided image. diff --git a/transformers/models/LFM2-VL-1.6B/run.py b/transformers/models/LFM2-VL-1.6B/run.py index a86b426..026b9ad 100644 --- a/transformers/models/LFM2-VL-1.6B/run.py +++ b/transformers/models/LFM2-VL-1.6B/run.py @@ -32,8 +32,6 @@ "max_image_tokens": 256, "do_image_splitting": True, } - - def main(): logging.basicConfig(level=logging.INFO, format="%(levelname)s %(message)s") args = get_arg_parser(MODEL_ID).parse_args() diff --git a/transformers/models/LFM2-VL-3B/run.py b/transformers/models/LFM2-VL-3B/run.py index b29bb57..94f7e7c 100644 --- a/transformers/models/LFM2-VL-3B/run.py +++ b/transformers/models/LFM2-VL-3B/run.py @@ -32,8 +32,6 @@ "max_image_tokens": 256, "do_image_splitting": True, } - - def main(): logging.basicConfig(level=logging.INFO, format="%(levelname)s %(message)s") args = get_arg_parser(MODEL_ID).parse_args() diff --git a/transformers/models/LFM2-VL-450M/run.py b/transformers/models/LFM2-VL-450M/run.py index 61b1a73..026218b 100644 --- a/transformers/models/LFM2-VL-450M/run.py +++ b/transformers/models/LFM2-VL-450M/run.py @@ -32,8 +32,6 @@ "max_image_tokens": 256, "do_image_splitting": True, } - - def main(): logging.basicConfig(level=logging.INFO, format="%(levelname)s %(message)s") args = get_arg_parser(MODEL_ID).parse_args() diff --git a/transformers/models/Qwen3-VL-2B-Instruct/run.py b/transformers/models/Qwen3-VL-2B-Instruct/run.py index ad7a93c..a42e2fd 100644 --- a/transformers/models/Qwen3-VL-2B-Instruct/run.py +++ b/transformers/models/Qwen3-VL-2B-Instruct/run.py @@ -28,8 +28,6 @@ # Qwen3-VL uses dynamic resolution — no special processor kwargs needed PROCESSOR_KWARGS = {} - - def main(): logging.basicConfig(level=logging.INFO, format="%(levelname)s %(message)s") args = get_arg_parser(MODEL_ID).parse_args() diff --git a/transformers/models/Qwen3-VL-4B-Instruct/run.py b/transformers/models/Qwen3-VL-4B-Instruct/run.py index b9368aa..7c14ff3 100644 --- a/transformers/models/Qwen3-VL-4B-Instruct/run.py +++ b/transformers/models/Qwen3-VL-4B-Instruct/run.py @@ -27,8 +27,6 @@ # Qwen3-VL uses dynamic resolution — no special processor kwargs needed PROCESSOR_KWARGS = {} - - def main(): logging.basicConfig(level=logging.INFO, format="%(levelname)s %(message)s") args = get_arg_parser(MODEL_ID).parse_args() diff --git a/transformers/models/gemma-3-4b-it/run.py b/transformers/models/gemma-3-4b-it/run.py index 066be86..db45a3b 100644 --- a/transformers/models/gemma-3-4b-it/run.py +++ b/transformers/models/gemma-3-4b-it/run.py @@ -30,8 +30,6 @@ PROCESSOR_KWARGS = { "padding_side": "left", } - - def main(): logging.basicConfig(level=logging.INFO, format="%(levelname)s %(message)s") args = get_arg_parser(MODEL_ID).parse_args() diff --git a/transformers/models/gemma-3-4b-pt/run.py b/transformers/models/gemma-3-4b-pt/run.py index 5755227..605bff6 100644 --- a/transformers/models/gemma-3-4b-pt/run.py +++ b/transformers/models/gemma-3-4b-pt/run.py @@ -30,8 +30,6 @@ PROCESSOR_KWARGS = { "padding_side": "left", } - - def main(): logging.basicConfig(level=logging.INFO, format="%(levelname)s %(message)s") args = get_arg_parser(MODEL_ID).parse_args() diff --git a/transformers/models/gemma-4-E2B-it/run.py b/transformers/models/gemma-4-E2B-it/run.py index 4882c59..165d358 100644 --- a/transformers/models/gemma-4-E2B-it/run.py +++ b/transformers/models/gemma-4-E2B-it/run.py @@ -30,8 +30,6 @@ PROCESSOR_KWARGS = { "padding_side": "left", } - - def main(): logging.basicConfig(level=logging.INFO, format="%(levelname)s %(message)s") args = get_arg_parser(MODEL_ID).parse_args() diff --git a/transformers/scripts/download_model.py b/transformers/scripts/download_model.py index bf2f4ad..3d23e50 100644 --- a/transformers/scripts/download_model.py +++ b/transformers/scripts/download_model.py @@ -1,5 +1,9 @@ #!/usr/bin/env python3 -"""Download a trained Ximilar VLM model artifact by UUID.""" +""" +Download a trained Ximilar VLM model artifact by UUID. + +RUN: uv run scripts/download_model.py --model-uuid --output-path +""" import argparse import sys