Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use BanUrsus/whisper-tiny-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BanUrsus/whisper-tiny-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="BanUrsus/whisper-tiny-en")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("BanUrsus/whisper-tiny-en") model = AutoModelForSpeechSeq2Seq.from_pretrained("BanUrsus/whisper-tiny-en", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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tags:
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- generated_from_trainer
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datasets:
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- minds14
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metrics:
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- wer
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model-index:
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- Transformers 4.39.2
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- Pytorch 1.13.0+cu117
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- Datasets 2.16.1
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- Tokenizers 0.15.1
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tags:
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- generated_from_trainer
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datasets:
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- PolyAI/minds14
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metrics:
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- wer
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model-index:
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- Transformers 4.39.2
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- Pytorch 1.13.0+cu117
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- Datasets 2.16.1
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- Tokenizers 0.15.1
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