Instructions to use BioMedTok/SentencePieceBPE-Wikipedia-FR-Morphemes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BioMedTok/SentencePieceBPE-Wikipedia-FR-Morphemes with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="BioMedTok/SentencePieceBPE-Wikipedia-FR-Morphemes")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("BioMedTok/SentencePieceBPE-Wikipedia-FR-Morphemes") model = AutoModelForMaskedLM.from_pretrained("BioMedTok/SentencePieceBPE-Wikipedia-FR-Morphemes", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2275342b774c759e936269eae06f67dbc9680b5b8f64d547dc89f72c2a3451b8
- Size of remote file:
- 885 MB
- SHA256:
- 756188d67318fa1a055950cf2eb569f5f323cdee0daa9b1649116d4903844808
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.