67 lines
1.8 KiB
Python
Executable File
67 lines
1.8 KiB
Python
Executable File
#!/usr/bin/env python
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from __future__ import annotations
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import os
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import sys
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from pathlib import Path
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from huggingface_hub import HfApi
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SOURCE_CACHE = (
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Path.home()
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/ ".cache/huggingface/hub/models--ibm-granite--granite-speech-4.1-2b-plus"
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)
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DEST_REPO = "mlx-community/granite-speech-4.1-2b-plus-mlx"
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def find_weights_dir(root: Path) -> Path | None:
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if not root.exists():
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return None
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if list(root.glob("*.safetensors")) or (root / "config.json").exists():
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return root
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snapshots = root / "snapshots"
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if snapshots.exists():
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candidates = [
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path
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for path in snapshots.iterdir()
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if path.is_dir() and (list(path.glob("*.safetensors")) or (path / "config.json").exists())
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]
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if candidates:
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return sorted(candidates, key=lambda p: p.stat().st_mtime)[-1]
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return None
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def print_manual_commands() -> None:
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print(f"MLX weights not found at {SOURCE_CACHE}")
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print("Create them first with:")
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print("mlxconv ibm-granite/granite-speech-4.1-2b-plus")
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print("mlxconv ibm-granite/granite-speech-4.1-2b-plus --dtype q4_k_4")
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def main() -> int:
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weights_dir = find_weights_dir(SOURCE_CACHE)
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if weights_dir is None:
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print_manual_commands()
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return 1
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token = os.environ.get("HF_TOKEN")
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if not token:
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print("HF_TOKEN is required to upload.", file=sys.stderr)
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return 2
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api = HfApi(token=token)
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api.create_repo(DEST_REPO, repo_type="model", exist_ok=True)
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api.upload_folder(
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repo_id=DEST_REPO,
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repo_type="model",
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folder_path=str(weights_dir),
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commit_message="Upload Granite Speech 4.1-2b-plus MLX weights",
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)
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print(f"Uploaded {weights_dir} to {DEST_REPO}")
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return 0
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if __name__ == "__main__":
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sys.exit(main())
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