Instructions to use BioMedTok/SentencePieceBPE-CC100-FR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BioMedTok/SentencePieceBPE-CC100-FR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="BioMedTok/SentencePieceBPE-CC100-FR")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("BioMedTok/SentencePieceBPE-CC100-FR") model = AutoModelForMaskedLM.from_pretrained("BioMedTok/SentencePieceBPE-CC100-FR", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from BioMedTok/SentencePieceBPE-CC100-FR: direct link, hf CLI and curl.
- Browser
- Download file 443 MB
-
https://huggingface.co/BioMedTok/SentencePieceBPE-CC100-FR/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://BioMedTok/SentencePieceBPE-CC100-FR/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/BioMedTok/SentencePieceBPE-CC100-FR/resolve/main/pytorch_model.bin
443 MB
- Xet hash:
- 4cc30998a36a940b295e28cf0f474a60a16824b69e8f3e0757a2b3a762387c28
- Size of remote file:
- 443 MB
- SHA256:
- be123c129964df40db7d97d394736497ccf0b283f4509e392d3d3cf1df88a2a6
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