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Lize CaiandGitHub
fab85e09c2
* update fluid kserve demo to use huggingface servingruntime and other model. Signed-off-by: Lize Cai <[email protected]> * fix lint Signed-off-by: Lize Cai <[email protected]> * explicitly set custom servingruntime, update devshm. Signed-off-by: Lize Cai <[email protected]> * update the args in custom kserve hfserver Signed-off-by: Lize Cai <[email protected]> * address comments Signed-off-by: Lize Cai <[email protected]> * add return of line Signed-off-by: Lize Cai <[email protected]> --------- Signed-off-by: Lize Cai <[email protected]>
53 lines
1.5 KiB
Python
53 lines
1.5 KiB
Python
# Copyright 2023, SAP SE or an SAP affiliate company and KServe contributors
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import argparse
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from pathlib import Path
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from huggingface_hub import snapshot_download
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if __name__ == "__main__":
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parser = argparse.ArgumentParser()
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parser.add_argument(
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"--model_name",
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default="bigscience/bloom-560m",
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help="model name from huggingface",
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)
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parser.add_argument(
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"--model_dir",
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default="./models",
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help="dir to download the model",
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)
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parser.add_argument(
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"--revision",
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default="main",
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help="revision of the model",
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)
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args = vars(parser.parse_args())
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model_name = args["model_name"]
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revision = args["revision"]
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out_dir = args["model_dir"]
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tmp_model_name = model_name.replace("/", "--")
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model_dir = Path(out_dir, f"models--{tmp_model_name}", "snapshots", revision)
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# check the model repo and update it accordingly
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allow_patterns = ["*.json", "*.safetensors", "*.model"]
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# here safetensors is the preferred format.
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ignore_patterns = ["*.msgpack", "*.h5", "*.bin"]
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# set the path to download the model
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models_path = Path(model_dir)
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models_path.mkdir(parents=True, exist_ok=True)
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# download the snapshot
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output_dir = snapshot_download(
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repo_id=model_name,
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revision=revision,
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allow_patterns=allow_patterns,
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ignore_patterns=ignore_patterns,
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local_dir=models_path,
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)
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print(output_dir)
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