Instructions to use Dandan0K/xls_1b_decoding_fr_decoding_phondel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dandan0K/xls_1b_decoding_fr_decoding_phondel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Dandan0K/xls_1b_decoding_fr_decoding_phondel")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Dandan0K/xls_1b_decoding_fr_decoding_phondel") model = AutoModelForCTC.from_pretrained("Dandan0K/xls_1b_decoding_fr_decoding_phondel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Dandan0K/xls_1b_decoding_fr_decoding_phondel: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/Dandan0K/xls_1b_decoding_fr_decoding_phondel/resolve/main/training_args.bin
- Command line
-
hf download hf://Dandan0K/xls_1b_decoding_fr_decoding_phondel/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Dandan0K/xls_1b_decoding_fr_decoding_phondel/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- b085d1a9f98f68abe7515869a030fde523254bcdcc50477c54db506d9e51a5f3
- Size of remote file:
- 5.11 kB
- SHA256:
- 9e7063247d124e1ee1d166a21328d7cf727480b1c604ec2b77f3f44a7a56e492
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