Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
English
wav2vec2-bert
mozilla-foundation/common_voice_16_0
Generated from Trainer
Instructions to use hf-audio/wav2vec2-bert-CV16-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-audio/wav2vec2-bert-CV16-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hf-audio/wav2vec2-bert-CV16-en")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("hf-audio/wav2vec2-bert-CV16-en") model = AutoModelForCTC.from_pretrained("hf-audio/wav2vec2-bert-CV16-en", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from hf-audio/wav2vec2-bert-CV16-en: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
-
https://huggingface.co/hf-audio/wav2vec2-bert-CV16-en/resolve/main/training_args.bin
- Command line
-
hf download hf://hf-audio/wav2vec2-bert-CV16-en/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/hf-audio/wav2vec2-bert-CV16-en/resolve/main/training_args.bin
4.73 kB
- Xet hash:
- 69f3e9b250e4bf10ba4bbe8172ebbd48f3038e69f9ebf31429a27a8616a9de67
- Size of remote file:
- 4.73 kB
- SHA256:
- 01f5f2269df47b0eb413353be5d5eebe907f765468dc3410a8bf5bc7ac445b94
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