Instructions to use Dandan0K/xls_1b_decoding_fr_decoding 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 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")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Dandan0K/xls_1b_decoding_fr_decoding") model = AutoModelForCTC.from_pretrained("Dandan0K/xls_1b_decoding_fr_decoding", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Dandan0K/xls_1b_decoding_fr_decoding: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/Dandan0K/xls_1b_decoding_fr_decoding/resolve/main/training_args.bin
- Command line
-
hf download hf://Dandan0K/xls_1b_decoding_fr_decoding/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Dandan0K/xls_1b_decoding_fr_decoding/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- 95d2de69d8a8d1a8d4a7bd5ae6e0e46de0d79c6cc0659da3227b608d74ee0bdf
- Size of remote file:
- 5.11 kB
- SHA256:
- 0b4f70f2a406f0d244e748626370a0e75afaffde653613aaa8fa09f63148a007
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