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 training_args.bin from Kuray107/librispeech-100h-supervised: direct link, hf CLI and curl.
- Browser
- Download file 2.93 kB
-
https://huggingface.co/Kuray107/librispeech-100h-supervised/resolve/main/training_args.bin
- Command line
-
hf download hf://Kuray107/librispeech-100h-supervised/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Kuray107/librispeech-100h-supervised/resolve/main/training_args.bin
2.93 kB
- Xet hash:
- 57337c8cd0b1a5fcf0f04875de8760862ff6eeebcbaa3ffe0a2f49fe8f9c5b74
- Size of remote file:
- 2.93 kB
- SHA256:
- b72e02321517fa5c28f95937c584cef7631cf52cbbd2b56ecb1882608ad3eafa
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