Instructions to use sagteam/xlm-roberta-large-sag with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sagteam/xlm-roberta-large-sag with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="sagteam/xlm-roberta-large-sag")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("sagteam/xlm-roberta-large-sag") model = AutoModelForMaskedLM.from_pretrained("sagteam/xlm-roberta-large-sag", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download sentencepiece.bpe.model from sagteam/xlm-roberta-large-sag: direct link, hf CLI and curl.
- Browser
- Download file 5.07 MB
-
https://huggingface.co/sagteam/xlm-roberta-large-sag/resolve/main/sentencepiece.bpe.model
- Command line
-
hf download hf://sagteam/xlm-roberta-large-sag/sentencepiece.bpe.model
-
curl -L -o sentencepiece.bpe.model https://huggingface.co/sagteam/xlm-roberta-large-sag/resolve/main/sentencepiece.bpe.model
5.07 MB
- Xet hash:
- 8b03b9e079abc849bdd27d0942fa6a77f9e7836db188512be97e4b3d52f415a8
- Size of remote file:
- 5.07 MB
- SHA256:
- cfc8146abe2a0488e9e2a0c56de7952f7c11ab059eca145a0a727afce0db2865
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