Instructions to use BioMedTok/SentencePieceBPE-Wikipedia-FR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BioMedTok/SentencePieceBPE-Wikipedia-FR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="BioMedTok/SentencePieceBPE-Wikipedia-FR")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("BioMedTok/SentencePieceBPE-Wikipedia-FR") model = AutoModelForMaskedLM.from_pretrained("BioMedTok/SentencePieceBPE-Wikipedia-FR", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download scheduler.pt from BioMedTok/SentencePieceBPE-Wikipedia-FR: direct link, hf CLI and curl.
- Browser
- Download file 623 Bytes
-
https://huggingface.co/BioMedTok/SentencePieceBPE-Wikipedia-FR/resolve/main/scheduler.pt
- Command line
-
hf download hf://BioMedTok/SentencePieceBPE-Wikipedia-FR/scheduler.pt
-
curl -L -o scheduler.pt https://huggingface.co/BioMedTok/SentencePieceBPE-Wikipedia-FR/resolve/main/scheduler.pt
623 Bytes
- Xet hash:
- 66f26ee075f215efb7bf319b5147d1e7802dc3f1217035b7c740a6533233d93e
- Size of remote file:
- 623 Bytes
- SHA256:
- f80bd60ea5ef20a59695f24c1be681c0bc9aac0cf8bd32bc600f83c9f8a68ec8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.