| |
| """Convert the pinned official Fun-ASR-Nano checkpoint to safetensors.""" |
|
|
| from __future__ import annotations |
|
|
| import argparse |
| import hashlib |
| from pathlib import Path |
|
|
| import torch |
| from safetensors.torch import save_file |
|
|
|
|
| SOURCE_REVISION = "272c57b82523ada6fd87095e955f8e29100979ab" |
| SOURCE_SHA256 = "55ae0d2fee369f0f11cce0795f6927934ad17cf11b278a7e56a51272074160bb" |
| EXPECTED_TENSORS = 1261 |
|
|
|
|
| def sha256(path: Path) -> str: |
| digest = hashlib.sha256() |
| with path.open("rb") as stream: |
| for chunk in iter(lambda: stream.read(16 * 1024 * 1024), b""): |
| digest.update(chunk) |
| return digest.hexdigest() |
|
|
|
|
| def main() -> None: |
| parser = argparse.ArgumentParser() |
| parser.add_argument("source", type=Path, help="Pinned official model.pt") |
| parser.add_argument("output", type=Path, help="Output model.safetensors") |
| args = parser.parse_args() |
|
|
| actual_source_hash = sha256(args.source) |
| if actual_source_hash != SOURCE_SHA256: |
| raise SystemExit( |
| f"source SHA-256 mismatch: expected {SOURCE_SHA256}, got {actual_source_hash}" |
| ) |
|
|
| checkpoint = torch.load(args.source, map_location="cpu", weights_only=True) |
| state_dict = checkpoint.get("state_dict", checkpoint) |
| if len(state_dict) != EXPECTED_TENSORS: |
| raise SystemExit( |
| f"tensor count mismatch: expected {EXPECTED_TENSORS}, got {len(state_dict)}" |
| ) |
| if not all(isinstance(value, torch.Tensor) for value in state_dict.values()): |
| raise SystemExit("checkpoint contains non-tensor state-dict values") |
|
|
| lora_keys = [key for key in state_dict if "lora" in key.lower()] |
| if lora_keys: |
| raise SystemExit(f"unexpected LoRA tensors: {lora_keys[:10]}") |
|
|
| args.output.parent.mkdir(parents=True, exist_ok=True) |
| |
| |
| save_file(state_dict, args.output) |
| print(f"wrote {args.output}") |
| print(f"sha256 {sha256(args.output)}") |
| print(f"tensors {len(state_dict)}") |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|