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3dd5e9fb62
3 changed files with 6 additions and 6 deletions
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@ -72,6 +72,7 @@ The main benefit of this method is that the build is reproducible since there is
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uv pip install --group pre_build --no-build-isolation
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uv pip install --group compile_xformers --no-build-isolation
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uv sync
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uv run python download_blt_weights.py
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uv run python demo.py "A BLT has"
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```
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6
demo.py
6
demo.py
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@ -11,6 +11,8 @@ from bytelatent.tokenizers.blt_tokenizer import BltTokenizer
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def main(prompt: str, model_name: str = "blt-1b"):
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assert model_name in ['blt-1b', 'blt-7b']
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model_name = model_name.replace('-', '_')
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distributed_args = DistributedArgs()
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distributed_args.configure_world()
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if not torch.distributed.is_initialized():
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@ -25,9 +27,7 @@ def main(prompt: str, model_name: str = "blt-1b"):
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patcher_args = train_cfg.data.patcher_args.model_copy(deep=True)
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patcher_args.realtime_patching = True
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print("Loading entropy model and patcher")
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patcher_args.entropy_model_checkpoint_dir = os.path.join(
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checkpoint_path, "entropy_model"
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)
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patcher_args.entropy_model_checkpoint_dir = os.path.join("hf-weights", "entropy_model")
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patcher = patcher_args.build()
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prompts = [prompt]
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outputs = generate_nocache(
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@ -4,11 +4,10 @@ import typer
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from huggingface_hub import snapshot_download
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def main(models: list[str] = ["blt-1b", "blt-7b"]):
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def main():
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if not os.path.exists("hf-weights"):
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os.makedirs("hf-weights")
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for model in models:
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snapshot_download(f"facebook/{model}", local_dir=f"hf-weights/{model}")
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snapshot_download(f"facebook/blt", local_dir=f"hf-weights")
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if __name__ == "__main__":
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