|
--- |
|
base_model: |
|
- openai/whisper-large-v3-turbo |
|
datasets: |
|
- mozilla-foundation/common_voice_17_0 |
|
- google/fleurs |
|
language: |
|
- th |
|
library_name: transformers |
|
pipeline_tag: automatic-speech-recognition |
|
--- |
|
|
|
```python |
|
from transformers import AutoModelForSpeechSeq2Seq, AutoProcessor, pipeline |
|
import torch |
|
MODEL_NAME = "FILM6912/whisper-large-v3-turbo-thai" |
|
|
|
device = "cuda:0" if torch.cuda.is_available() else "cpu" |
|
torch_dtype = torch.float16 if torch.cuda.is_available() else torch.float32 |
|
|
|
model = AutoModelForSpeechSeq2Seq.from_pretrained( |
|
MODEL_NAME, |
|
torch_dtype=torch_dtype, |
|
# low_cpu_mem_usage=True, |
|
# use_safetensors=True, |
|
) |
|
model.to(device) |
|
processor = AutoProcessor.from_pretrained(MODEL_NAME) |
|
|
|
whisper = pipeline( |
|
"automatic-speech-recognition", |
|
model=model, |
|
tokenizer=processor.tokenizer, |
|
feature_extractor=processor.feature_extractor, |
|
max_new_tokens=128, |
|
torch_dtype=torch_dtype, |
|
device=device, |
|
) |
|
|
|
whisper("c.mp3", |
|
chunk_length_s=30, |
|
stride_length_s=5, |
|
batch_size=16, |
|
return_timestamps=True, |
|
generate_kwargs = {"language":"th"} |
|
) |
|
``` |
|
|
|
|