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