Instructions to use BioMedTok/BPE-HF-NACHOS-FR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BioMedTok/BPE-HF-NACHOS-FR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="BioMedTok/BPE-HF-NACHOS-FR")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("BioMedTok/BPE-HF-NACHOS-FR") model = AutoModelForMaskedLM.from_pretrained("BioMedTok/BPE-HF-NACHOS-FR", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from BioMedTok/BPE-HF-NACHOS-FR: direct link, hf CLI and curl.
- Browser
- Download file 885 MB
-
https://huggingface.co/BioMedTok/BPE-HF-NACHOS-FR/resolve/main/optimizer.pt
- Command line
-
hf download hf://BioMedTok/BPE-HF-NACHOS-FR/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/BioMedTok/BPE-HF-NACHOS-FR/resolve/main/optimizer.pt
885 MB
- Xet hash:
- ee21659e832c001c9933e62e72a4de39db6db51de53933003bfa25288a022f68
- Size of remote file:
- 885 MB
- SHA256:
- eb8dfaabc62c44c39ed4908a917fe1983c4ad3a804fe7665d23908380433434c
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