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Update app.py
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app.py
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# Use a pipeline as a high-level helper
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from transformers import pipeline
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pipe = pipeline("text-generation", model="scb10x/llama-3-typhoon-v1.5-8b-audio-preview", trust_remote_code=True)
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from transformers import AutoModel
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# Initialize from the trained model
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model = AutoModel.from_pretrained(
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"scb10x/llama-3-typhoon-v1.5-8b-audio-preview",
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torch_dtype=torch.float16,
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trust_remote_code=True
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)
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model.to("cuda")
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model.eval()
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# Run generation
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prompt_pattern="<|begin_of_text|><|start_header_id|>user<|end_header_id|>\n\n<Speech><SpeechHere></Speech> {}<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n"
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response = model.generate(
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wav_path="path_to_your_audio.wav",
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prompt="transcribe this audio",
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prompt_pattern=prompt_pattern,
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do_sample=False,
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max_length=1200,
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repetition_penalty=1.1,
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num_beams=1,
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# temperature=0.4,
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# top_p=0.9,
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# streamer=streamer # supports TextIteratorStreamer
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)
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print(response)
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