Fabio
c36510c21e
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72 lines
3.1 KiB
Python
72 lines
3.1 KiB
Python
#!/usr/bin/env python3
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"""Convert an official Hugging Face GigaAM ASR snapshot to a self-contained GGUF."""
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import argparse
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import json
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import shutil
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import subprocess
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from pathlib import Path
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import torch
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from safetensors.torch import save_file
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VARIANTS = (
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"v3_ctc", "v3_rnnt", "v3_e2e_ctc", "v3_e2e_rnnt",
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"multilingual_ctc", "multilingual_large_ctc",
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)
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def main():
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parser = argparse.ArgumentParser(description=__doc__)
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parser.add_argument("source", type=Path, help="Local Hugging Face model snapshot")
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parser.add_argument("output", type=Path)
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parser.add_argument("--staging-dir", required=True, type=Path)
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parser.add_argument("--converter", type=Path, default=Path("build/debug/bin/audiocpp_gguf"))
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parser.add_argument("--spec", type=Path, default=Path("model_specs/gigaam_asr.json"))
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parser.add_argument("--overwrite", action="store_true")
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parser.add_argument("--type", choices=["orig", "f16"], default="orig",
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help="Original precision, or F16 weights with F32 frontend and normalization")
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args = parser.parse_args()
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config = json.loads((args.source / "config.json").read_text())["cfg"]["model"]["cfg"]
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variant = config["model_name"]
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if variant not in VARIANTS:
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raise ValueError(f"Unsupported ASR variant: {variant}")
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original = torch.load(args.source / "pytorch_model.bin", map_location="cpu", weights_only=True)
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state = {name.removeprefix("model."): value for name, value in original.items()}
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if not any(name.startswith("head.") for name in state):
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raise ValueError("Expected a fine-tuned ASR checkpoint, not an SSL encoder")
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uses_sentencepiece = bool(config["decoding"].get("model_path"))
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args.staging_dir.mkdir(parents=True, exist_ok=True)
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tensors = {name: value.detach().cpu().contiguous().clone() for name, value in state.items()}
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save_file(tensors, args.staging_dir / "model.safetensors")
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config["decoding"]["model_path"] = "tokenizer.model" if uses_sentencepiece else None
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(args.staging_dir / "config.json").write_text(json.dumps(config, indent=2) + "\n")
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if uses_sentencepiece:
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shutil.copyfile(args.source / "tokenizer.model", args.staging_dir / "tokenizer.model")
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args.output.parent.mkdir(parents=True, exist_ok=True)
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command = [
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str(args.converter.resolve()),
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"--input", str(args.staging_dir / "model.safetensors"),
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"--output", str(args.output), "--type", args.type,
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"--family", "gigaam_asr", "--model-spec", str(args.spec),
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"--root", str(args.staging_dir),
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"--sidecar", f"{args.staging_dir / 'config.json'}=config.json",
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]
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if args.type == "f16":
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command += ["--keep-type", "preprocessor.*=f32"]
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for name, tensor in tensors.items():
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if tensor.ndim == 1:
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command += ["--keep-type", f"{name}*=f32"]
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if uses_sentencepiece:
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command += ["--sidecar", f"{args.staging_dir / 'tokenizer.model'}=tokenizer.model"]
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if args.overwrite:
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command += ["--overwrite"]
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subprocess.run(command, check=True)
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print(f"Converted {variant}: {len(tensors)} tensors, storage={args.type}")
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if __name__ == "__main__":
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main()
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