Fun-ASR-Nano-2512-vllm / convert_from_official.py
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Publish official vLLM-native Fun-ASR-Nano-2512 package
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#!/usr/bin/env python3
"""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)
# Keep provenance in MODEL_PROVENANCE.json. safetensors serializes metadata
# map keys in nondeterministic order, which would make whole-file hashes vary.
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()