Automatic Speech Recognition
MLX
PyTorch
TensorFlow
Safetensors
English
wav2vec2
audio
hf-asr-leaderboard
Eval Results (legacy)
Instructions to use HashNuke/wav2vec2-base-960h-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use HashNuke/wav2vec2-base-960h-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir wav2vec2-base-960h-mlx HashNuke/wav2vec2-base-960h-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
Commit ·
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Parent(s): 5e3d456
Update README.md
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README.md
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tags:
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- audio
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- automatic-speech-recognition
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license: apache-2.0
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widget:
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- example_title: Librispeech sample 1
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src: https://cdn-media.huggingface.co/speech_samples/sample1.flac
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- example_title: Librispeech sample 2
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src: https://cdn-media.huggingface.co/speech_samples/sample2.flac
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---
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# Wav2Vec2-Base-960h
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tags:
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- audio
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- automatic-speech-recognition
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- hf-asr-leaderboard
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license: apache-2.0
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widget:
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- example_title: Librispeech sample 1
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src: https://cdn-media.huggingface.co/speech_samples/sample1.flac
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- example_title: Librispeech sample 2
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src: https://cdn-media.huggingface.co/speech_samples/sample2.flac
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model-index:
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- name: wav2vec2-base-960h
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results:
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- task:
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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: Librispeech (clean)
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type: librispeech_asr
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args: en
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metrics:
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- name: Test WER
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type: wer
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value: 3.4
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- task:
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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: Librispeech (other)
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type: librispeech_asr
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args: en
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metrics:
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- name: Test WER
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type: wer
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value: 8.6
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---
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# Wav2Vec2-Base-960h
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