[contrib] Add MPT-7B-Chat NeuronX port

contrib/models/mpt-7b-chat/README.md

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+# Contrib Model: MPT-7B-Chat
+
+NeuronX Distributed Inference implementation of MosaicML MPT-7B-Chat.
+
+## Model Information
+
+- **HuggingFace ID:** `mosaicml/mpt-7b-chat`
+- **Model Type:** Decoder-only transformer with ALiBi attention
+- **Parameters:** 6.7B
+- **License:** CC-BY-SA-3.0
+
+## Architecture Details
+
+| Property | Value |
+|----------|-------|
+| Hidden Size | 4096 |
+| Num Attention Heads | 32 (MHA) |
+| Head Dimension | 128 |
+| Num Hidden Layers | 32 |
+| Vocab Size | 50432 |
+| Max Position Embeddings | 2048 |
+| Intermediate Size | 16384 |
+| Position Encoding | ALiBi (Attention with Linear Biases) |
+| Residual Connection | Sequential (LN -> Attn -> Add -> LN -> MLP -> Add) |
+| Normalization | LayerNorm without bias (eps=1e-5) |
+| Activation | GELU |
+| LM Head | Tied to token embeddings |
+
+### Key Implementation Notes
+
+- **ALiBi attention:** NXDI has no native ALiBi support. Per-head slopes are stored as a weight parameter (`alibi_slopes`) that gets TP-sharded with attention heads. Position bias is computed at runtime from slopes and token positions, then added to attention scores before softmax.
+- **Flash attention disabled:** NKI kernels cannot accept additive bias tensors, so flash attention must be disabled for ALiBi to work.
+- **Fused QKV:** HF checkpoint stores a single `Wqkv` weight. During weight conversion, this is split into separate Q, K, V projections.
+- **No-bias LayerNorm:** MPT uses `no_bias=True` for all LayerNorm layers.
+
+## Validation Results
+
+**Validated:** 2026-03-05
+**Configuration:** TP=1, batch_size=1, seq_len=128, bfloat16
+
+### Test Results
+
+| Test | Status | Result |
+|------|--------|--------|
+| Smoke Test | PASS | Model loads successfully |
+| Greedy Token Matching | PASS | **54.84% average** (2/10 prompts at 100%) |
+| Teacher-Forced Match | PASS | **97.50% average** |
+
+### Greedy Match Details
+
+2 of 10 prompts achieve 100% greedy match (quadratic equation and fibonacci code). The lower greedy match rate compared to non-ALiBi models is expected: BF16 precision differences in the additive position bias compound during autoregressive generation. The high teacher-forced rate (97.50%) confirms weights are correctly ported.
+
+## Usage
+
+```python
+from transformers import AutoTokenizer
+from neuronx_distributed_inference.models.config import NeuronConfig
+
+from src.modeling_mpt import NeuronMptForCausalLM, MptInferenceConfig
+
+model_path = "/path/to/mpt-7b-chat/"
+compiled_model_path = "/path/to/compiled/"
+
+# Configure
+neuron_config = MptInferenceConfig.get_neuron_config_cls()(
+    tp_degree=1,
+    batch_size=1,
+    seq_len=128,
+    torch_dtype=torch.bfloat16,
+)
+
+config = MptInferenceConfig.from_pretrained(
+    model_path,
+    neuron_config=neuron_config,
+)
+
+# Compile and load
+model = NeuronMptForCausalLM(model_path, config)
+model.compile(compiled_model_path)
+model.load(compiled_model_path)
+
+# Generate
+tokenizer = AutoTokenizer.from_pretrained(model_path)
+# ... (see integration test for full example)
+```
+
+## Performance
+
+Profiled on trn1.32xlarge (single NeuronCore utilization):
+
+| Metric | Context Encoding | Token Generation |
+|--------|-----------------|------------------|
+| Throughput | - | 18.0 tok/s |
+| MBU (Memory) | 18.9% | 17.2% |
+| MFU (Compute) | 10.3% | 0.1% |
+
+*Batch size 1, sequence length 128, BF16 precision, TP=1*
+## Compatibility Matrix
+
+| Instance/Version | 2.20+ | 2.19 and earlier |
+|------------------|-------|------------------|
+| Trn1             | Working | Not tested |
+| Inf2             | Not tested | Not tested |
+
+## Testing
+
+Run integration tests:
+
+```bash
+pytest contrib/models/mpt-7b-chat/test/integration/test_model.py --capture=tee-sys
+```
+
+## Example Checkpoints
+
+* mosaicml/mpt-7b-chat
+
+## Maintainer
+
+Neuroboros Team - Annapurna Labs
+
+**Last Updated:** 2026-03-05

contrib/models/mpt-7b-chat/src/__init__.py

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+from .modeling_mpt import NeuronMptForCausalLM, MptInferenceConfig
+
+__all__ = ["NeuronMptForCausalLM", "MptInferenceConfig"]