Instructions to use BioMedTok/SentencePieceBPE-NACHOS-FR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BioMedTok/SentencePieceBPE-NACHOS-FR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="BioMedTok/SentencePieceBPE-NACHOS-FR")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("BioMedTok/SentencePieceBPE-NACHOS-FR") model = AutoModelForMaskedLM.from_pretrained("BioMedTok/SentencePieceBPE-NACHOS-FR", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from BioMedTok/SentencePieceBPE-NACHOS-FR: direct link, hf CLI and curl.
- Browser
- Download file 885 MB
-
https://huggingface.co/BioMedTok/SentencePieceBPE-NACHOS-FR/resolve/refs%2Fpr%2F1/optimizer.pt
- Command line
-
hf download hf://BioMedTok/SentencePieceBPE-NACHOS-FR@refs/pr/1/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/BioMedTok/SentencePieceBPE-NACHOS-FR/resolve/refs%2Fpr%2F1/optimizer.pt
885 MB
- Xet hash:
- 12d94344ed86be511f5f3edcc395051b35dffa1afafdd78b27b2858133019781
- Size of remote file:
- 885 MB
- SHA256:
- c0381c9b592b08e8cfd27e64d729f2369cb267b1d3f164e36117dec55e7a87d1
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