File size: 1,246 Bytes
6b0949d c882bc1 6b0949d e3003d0 c882bc1 6b0949d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 | import torch
from transformers import AutoModelForSpeechSeq2Seq, AutoProcessor, pipeline
def transcribe(audio_path, translate):
device = "cuda:0" if torch.cuda.is_available() else "cpu"
torch_dtype = torch.float16 if torch.cuda.is_available() else torch.float32
model_id = "openai/whisper-large-v3"
model = AutoModelForSpeechSeq2Seq.from_pretrained(
model_id, torch_dtype=torch_dtype, low_cpu_mem_usage=True, use_safetensors=True
)
model.to(device)
processor = AutoProcessor.from_pretrained(model_id)
pipe = pipeline(
"automatic-speech-recognition",
model=model,
tokenizer=processor.tokenizer,
feature_extractor=processor.feature_extractor,
max_new_tokens=128,
chunk_length_s=30,
batch_size=16,
return_timestamps=True,
torch_dtype=torch_dtype,
device=device,
)
options = {"task": "translate"} if translate else {"language": "polish"}
print(f"Rozpoczęto tranksrypcję pliku {audio_path} z opcjami {options}")
result = pipe(audio_path, generate_kwargs=options)
print(f"Transkrypacja zakończona: {result}")
text = [chunk.get('text') for chunk in result["chunks"]]
return ''.join(map(str,text)) |