Automatic Speech Recognition
Transformers
PyTorch
wav2vec2
mozilla-foundation/common_voice_8_0
Generated from Trainer
Instructions to use anuragshas/wav2vec2-xls-r-300m-pa-IN-cv8-with-lm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anuragshas/wav2vec2-xls-r-300m-pa-IN-cv8-with-lm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="anuragshas/wav2vec2-xls-r-300m-pa-IN-cv8-with-lm")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("anuragshas/wav2vec2-xls-r-300m-pa-IN-cv8-with-lm") model = AutoModelForCTC.from_pretrained("anuragshas/wav2vec2-xls-r-300m-pa-IN-cv8-with-lm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from anuragshas/wav2vec2-xls-r-300m-pa-IN-cv8-with-lm: direct link, hf CLI and curl.
- Browser
- Download file 1.26 GB
-
https://huggingface.co/anuragshas/wav2vec2-xls-r-300m-pa-IN-cv8-with-lm/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://anuragshas/wav2vec2-xls-r-300m-pa-IN-cv8-with-lm/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/anuragshas/wav2vec2-xls-r-300m-pa-IN-cv8-with-lm/resolve/main/pytorch_model.bin
1.26 GB
- Xet hash:
- 059808bd704c2869db4f246eda407c578264f3b51dd44b2eff1a1ec729bc9d4d
- Size of remote file:
- 1.26 GB
- SHA256:
- 02803a923b958f334a82bd6d86d926aa900fcd2e03b7db1d5b8c0134285712a2
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