forked from phoenix-oss/llama-stack-mirror
530d4bdfe1
# 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 ```
67 lines
1.8 KiB
Python
Executable file
67 lines
1.8 KiB
Python
Executable file
#!/usr/bin/env python
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# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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# Run this script:
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# torchrun --nproc_per_node=8 scripts/generate_prompt_format.py meta-llama/Llama-4-17B-Omni-Instruct-BF16-16E ~/.llama/checkpoints/Llama-4-17B-Omni-Instruct-BF16-16E/ llama_stack.models.llama.llama4.prompts llama_stack/models/llama/llama4/prompt_format.md
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import importlib
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import os
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from pathlib import Path
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import fire
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from llama_stack.models.llama.llama3.generation import Llama3
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from llama_stack.models.llama.llama4.generation import Llama4
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from llama_stack.models.llama.sku_list import resolve_model
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THIS_DIR = Path(__file__).parent.resolve()
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def run_main(
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model_id: str,
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checkpoint_dir: str,
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module_name: str,
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output_path: str,
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llama4: bool = True,
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):
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module = importlib.import_module(module_name)
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assert hasattr(module, "usecases"), f"Module {module_name} missing usecases function"
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llama_model = resolve_model(model_id)
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if not llama_model:
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raise ValueError(f"Model {model_id} not found")
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cls = Llama4 if llama4 else Llama3
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generator = cls.build(
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ckpt_dir=checkpoint_dir,
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max_seq_len=4096,
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max_batch_size=1,
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)
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use_cases = module.usecases()
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text = ""
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for u in use_cases:
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if isinstance(u, str):
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use_case_text = f"\n{u}\n"
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else:
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use_case_text = u.to_text(generator)
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text += use_case_text
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print(use_case_text)
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os.makedirs(os.path.dirname(output_path), exist_ok=True)
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with open(output_path, "w") as f:
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f.write(text)
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def main():
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fire.Fire(run_main)
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if __name__ == "__main__":
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main()
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