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refactor: move all llama code to models/llama out of meta reference (#1887)

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# What does this PR do?

Move around bits. This makes the copies from llama-models _much_ easier
to maintain and ensures we don't entangle meta-reference specific
tidbits into llama-models code even by accident.

Also, kills the meta-reference-quantized-gpu distro and rolls
quantization deps into meta-reference-gpu.

## Test Plan

```
LLAMA_MODELS_DEBUG=1 \
  with-proxy llama stack run meta-reference-gpu \
  --env INFERENCE_MODEL=meta-llama/Llama-4-Scout-17B-16E-Instruct \
   --env INFERENCE_CHECKPOINT_DIR=<DIR> \
   --env MODEL_PARALLEL_SIZE=4 \
   --env QUANTIZATION_TYPE=fp8_mixed
```

Start a server with and without quantization. Point integration tests to
it using:

```
pytest -s -v  tests/integration/inference/test_text_inference.py \
   --stack-config http://localhost:8321 --text-model meta-llama/Llama-4-Scout-17B-16E-Instruct
```
This commit is contained in:
Ashwin Bharambe 2025-04-07 15:03:58 -07:00 • committed by GitHub
parent c52ccc4bbd
commit 530d4bdfe1
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85 changed files with 1267 additions and 1683 deletions
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45
llama_stack/templates/dependencies.json
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@ -356,50 +356,7 @@
"fairscale",
"faiss-cpu",
"fastapi",
"fire",
"httpx",
"langdetect",
"lm-format-enforcer",
"matplotlib",
"mcp",
"nltk",
"numpy",
"openai",
"opentelemetry-exporter-otlp-proto-http",
"opentelemetry-sdk",
"pandas",
"pillow",
"psycopg2-binary",
"pymongo",
"pypdf",
"pythainlp",
"redis",
"requests",
"scikit-learn",
"scipy",
"sentence-transformers",
"sentencepiece",
"torch",
"torchvision",
"tqdm",
"transformers",
"tree_sitter",
"uvicorn",
"zmq"
],
"meta-reference-quantized-gpu": [
"accelerate",
"aiosqlite",
"autoevals",
"blobfile",
"chardet",
"chromadb-client",
"datasets",
"emoji",
"fairscale",
"faiss-cpu",
"fastapi",
"fbgemm-gpu",
"fbgemm-gpu-genai==1.1.2",
"fire",
"httpx",
"langdetect",