Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Swedish
whisper
hf-asr-leaderboard
Generated from Trainer
Instructions to use Neprox/model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Neprox/model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Neprox/model")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Neprox/model") model = AutoModelForSpeechSeq2Seq.from_pretrained("Neprox/model") - Notebooks
- Google Colab
- Kaggle
update model card README.md
Browse files
README.md
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name:
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type: mozilla-foundation/common_voice_11_0
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config: null
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split: None
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# Whisper Small - Swedish
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the
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It achieves the following results on the evaluation set:
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- Loss: 0.3011
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- Wer: 19.8220
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: mozilla-foundation/common_voice_11_0
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type: mozilla-foundation/common_voice_11_0
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config: null
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split: None
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# Whisper Small - Swedish
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3011
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- Wer: 19.8220
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