Instructions to use Kuray107/librispeech-100h-supervised with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kuray107/librispeech-100h-supervised with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Kuray107/librispeech-100h-supervised")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Kuray107/librispeech-100h-supervised") model = AutoModelForCTC.from_pretrained("Kuray107/librispeech-100h-supervised", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Kuray107/librispeech-100h-supervised: direct link, hf CLI and curl.
- Browser
- Download file 1.26 GB
-
https://huggingface.co/Kuray107/librispeech-100h-supervised/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Kuray107/librispeech-100h-supervised/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Kuray107/librispeech-100h-supervised/resolve/main/pytorch_model.bin
1.26 GB
- Xet hash:
- 6a421c41164a6b3e4ab31f6384c845154426fbab492fcae580f4120a3fd34ed7
- Size of remote file:
- 1.26 GB
- SHA256:
- b8b63dab8631c911bc2f00ceb68475a6dfdc7f00d0c9b3cf5735cb0f9fec94de
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