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Add hf_hub_download #74

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NielsRogge Sep 30, 2024
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14 changes: 8 additions & 6 deletions README.md
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Expand Up @@ -39,25 +39,27 @@ This repository is the official implementation of Long-CLIP

Our model is based on [CLIP](https://github.com/openai/CLIP), please prepare environment for CLIP.


### how to use

Please first clone our [repo](https://github.com/beichenzbc/Long-CLIP) from github by running the following command.
Next, clone our [repo](https://github.com/beichenzbc/Long-CLIP) from Github by running the following command.

```shell
git clone https://github.com/beichenzbc/Long-CLIP.git
cd Long-CLIP
```

Then, download the checkpoints of our model [LongCLIP-B](https://huggingface.co/BeichenZhang/LongCLIP-B) and/or [LongCLIP-L](https://huggingface.co/BeichenZhang/LongCLIP-L) and place it under `./checkpoints`
### how to use

Then, download the checkpoints of our model [LongCLIP-B](https://huggingface.co/BeichenZhang/LongCLIP-B) and/or [LongCLIP-L](https://huggingface.co/BeichenZhang/LongCLIP-L) from 🤗 Hugging Face as shown below:

```python
from model import longclip
import torch
from PIL import Image
from huggingface_hub import hf_hub_download

device = "cuda" if torch.cuda.is_available() else "cpu"
model, preprocess = longclip.load("./checkpoints/longclip-B.pt", device=device)
# here we download LongCLIP-L
filepath = hf_hub_download(repo_id="BeichenZhang/LongCLIP-L", filename="longclip-L.pt")
model, preprocess = longclip.load(filepath, device=device)

text = longclip.tokenize(["A man is crossing the street with a red car parked nearby.", "A man is driving a car in an urban scene."]).to(device)
image = preprocess(Image.open("./img/demo.png")).unsqueeze(0).to(device)
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