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
- Atomic Chat
Download preprocessor_config.json from HashNuke/wav2vec2-base-960h-mlx: direct link, hf CLI and curl.
- Browser
- Download file 159 Bytes
-
https://huggingface.co/HashNuke/wav2vec2-base-960h-mlx/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://HashNuke/wav2vec2-base-960h-mlx/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/HashNuke/wav2vec2-base-960h-mlx/resolve/main/preprocessor_config.json
159 Bytes
| { | |
| "do_normalize": true, | |
| "feature_size": 1, | |
| "padding_side": "right", | |
| "padding_value": 0.0, | |
| "return_attention_mask": false, | |
| "sampling_rate": 16000 | |
| } | |