forked from phoenix-oss/llama-stack-mirror
93 lines
2.6 KiB
Python
Executable file
93 lines
2.6 KiB
Python
Executable file
#!/usr/bin/env python
|
|
# Copyright (c) Meta Platforms, Inc. and affiliates.
|
|
# All rights reserved.
|
|
#
|
|
# This source code is licensed under the terms described in the LICENSE file in
|
|
# the root directory of this source tree.
|
|
|
|
# Copyright (c) Meta Platforms, Inc. and affiliates.
|
|
# All rights reserved.
|
|
#
|
|
# This source code is licensed under the terms described in the LICENSE file in
|
|
# top-level folder for each specific model found within the models/ directory at
|
|
# the top-level of this source tree.
|
|
|
|
# Run this script:
|
|
# 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
|
|
|
|
|
|
import importlib
|
|
import os
|
|
from pathlib import Path
|
|
|
|
import fire
|
|
|
|
from llama_stack.models.llama.sku_list import resolve_model
|
|
from llama_stack.providers.inline.inference.meta_reference.config import (
|
|
MetaReferenceInferenceConfig,
|
|
)
|
|
from llama_stack.providers.inline.inference.meta_reference.llama3.generation import (
|
|
Llama3,
|
|
)
|
|
from llama_stack.providers.inline.inference.meta_reference.llama4.generation import (
|
|
Llama4,
|
|
)
|
|
|
|
THIS_DIR = Path(__file__).parent.resolve()
|
|
|
|
|
|
def run_main(
|
|
model_id: str,
|
|
checkpoint_dir: str,
|
|
module_name: str,
|
|
output_path: str,
|
|
llama4: bool = True,
|
|
):
|
|
module = importlib.import_module(module_name)
|
|
assert hasattr(module, "usecases"), f"Module {module_name} missing usecases function"
|
|
|
|
llama_model = resolve_model(model_id)
|
|
if not llama_model:
|
|
raise ValueError(f"Model {model_id} not found")
|
|
|
|
if not llama4:
|
|
config = MetaReferenceInferenceConfig(
|
|
model=model_id,
|
|
max_seq_len=4096,
|
|
max_batch_size=1,
|
|
checkpoint_dir=checkpoint_dir,
|
|
)
|
|
generator = Llama3.build(
|
|
config=config,
|
|
model_id=model_id,
|
|
llama_model=llama_model,
|
|
)
|
|
else:
|
|
generator = Llama4.build(
|
|
ckpt_dir=checkpoint_dir,
|
|
max_seq_len=4096,
|
|
max_batch_size=1,
|
|
)
|
|
|
|
use_cases = module.usecases()
|
|
text = ""
|
|
for u in use_cases:
|
|
if isinstance(u, str):
|
|
use_case_text = f"\n{u}\n"
|
|
else:
|
|
use_case_text = u.to_text(generator)
|
|
|
|
text += use_case_text
|
|
print(use_case_text)
|
|
|
|
os.makedirs(os.path.dirname(output_path), exist_ok=True)
|
|
with open(output_path, "w") as f:
|
|
f.write(text)
|
|
|
|
|
|
def main():
|
|
fire.Fire(run_main)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
main()
|