Create README.md
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README.md
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---
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language:
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- sv
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pipeline_tag: automatic-speech-recognition
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license: apache-2.0
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datasets:
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- KBLab/rixvox-v2
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---
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## KB-Whisper Medium
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The National Library of Sweden releases a new suite of Whisper models trained on over 50,000 hours of Swedish speech.
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### Usage
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```python
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import torch
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from datasets import load_dataset
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from transformers import AutoModelForSpeechSeq2Seq, AutoProcessor, pipeline
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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_id = "KBLab/kb-whisper-medium"
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model = AutoModelForSpeechSeq2Seq.from_pretrained(
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model_id, torch_dtype=torch_dtype, use_safetensors=True, cache_dir="cache"
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)
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model.to(device)
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processor = AutoProcessor.from_pretrained(model_id)
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pipe = 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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torch_dtype=torch_dtype,
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device=device,
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)
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generate_kwargs = {"task": "transcribe", "language": "sv"}
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# Add return_timestamps=True for output with timestamps
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res = pipe("audio.mp3",
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chunk_length_s=30,
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generate_kwargs={"task": "transcribe", "language": "sv"})
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```
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