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 added_tokens.json from Dandan0K/xls_1b_decoding_fr_decoding_phondel: direct link, hf CLI and curl.
- Browser
- Download file 30 Bytes
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https://huggingface.co/Dandan0K/xls_1b_decoding_fr_decoding_phondel/resolve/main/added_tokens.json
- Command line
-
hf download hf://Dandan0K/xls_1b_decoding_fr_decoding_phondel/added_tokens.json
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curl -L -o added_tokens.json https://huggingface.co/Dandan0K/xls_1b_decoding_fr_decoding_phondel/resolve/main/added_tokens.json
30 Bytes
| { | |
| "</s>": 35, | |
| "<s>": 34 | |
| } | |