Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
wav2vec2-bert
librispeech_asr
Generated from Trainer
Instructions to use ylacombe/wav2vec2-bert-CV16-en-libri with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ylacombe/wav2vec2-bert-CV16-en-libri with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ylacombe/wav2vec2-bert-CV16-en-libri")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("ylacombe/wav2vec2-bert-CV16-en-libri") model = AutoModelForCTC.from_pretrained("ylacombe/wav2vec2-bert-CV16-en-libri", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ylacombe/wav2vec2-bert-CV16-en-libri: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
-
https://huggingface.co/ylacombe/wav2vec2-bert-CV16-en-libri/resolve/main/training_args.bin
- Command line
-
hf download hf://ylacombe/wav2vec2-bert-CV16-en-libri/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ylacombe/wav2vec2-bert-CV16-en-libri/resolve/main/training_args.bin
4.73 kB
- Xet hash:
- 310ed0a0b07a2ecca7e1aa47701d91b73da1517b36ffbeda8a1a7bbf64450fd6
- Size of remote file:
- 4.73 kB
- SHA256:
- 5ebf3af626bc4231f97b52ab59ecf4d67b12030d2c206e018fa586a5e961ce3e
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