Instructions to use BioMedTok/SentencePieceBPE-NACHOS-FR-Morphemes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BioMedTok/SentencePieceBPE-NACHOS-FR-Morphemes with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="BioMedTok/SentencePieceBPE-NACHOS-FR-Morphemes")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("BioMedTok/SentencePieceBPE-NACHOS-FR-Morphemes") model = AutoModelForMaskedLM.from_pretrained("BioMedTok/SentencePieceBPE-NACHOS-FR-Morphemes", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from BioMedTok/SentencePieceBPE-NACHOS-FR-Morphemes: direct link, hf CLI and curl.
- Browser
- Download file 885 MB
-
https://huggingface.co/BioMedTok/SentencePieceBPE-NACHOS-FR-Morphemes/resolve/main/optimizer.pt
- Command line
-
hf download hf://BioMedTok/SentencePieceBPE-NACHOS-FR-Morphemes/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/BioMedTok/SentencePieceBPE-NACHOS-FR-Morphemes/resolve/main/optimizer.pt
885 MB
- Xet hash:
- c8329dc2737304ce36bf6f457f61e84137b8f47518de9cea49499d5963d1650b
- Size of remote file:
- 885 MB
- SHA256:
- cf90a6824b33bfcded22af4c73e79a4dc11ecf4c89e73020cef203781b426549
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