Instructions to use morit/french_xlm_xnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use morit/french_xlm_xnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="morit/french_xlm_xnli")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("morit/french_xlm_xnli") model = AutoModelForSequenceClassification.from_pretrained("morit/french_xlm_xnli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from morit/french_xlm_xnli: direct link, hf CLI and curl.
- Browser
- Download file 3.45 kB
-
https://huggingface.co/morit/french_xlm_xnli/resolve/main/training_args.bin
- Command line
-
hf download hf://morit/french_xlm_xnli/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/morit/french_xlm_xnli/resolve/main/training_args.bin
3.45 kB
- Xet hash:
- ddde6d2169d8dfa22a3a2985299403af840eebab96b9bc599b292171993602c5
- Size of remote file:
- 3.45 kB
- SHA256:
- e059f080d4e91e3a8f0f818ad51757cfee5dfa85b244eaef3db076c8da4f3976
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.