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 pytorch_model.bin from sagteam/xlm-roberta-large-sag: direct link, hf CLI and curl.
- Browser
- Download file 2.24 GB
-
https://huggingface.co/sagteam/xlm-roberta-large-sag/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://sagteam/xlm-roberta-large-sag/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/sagteam/xlm-roberta-large-sag/resolve/main/pytorch_model.bin
2.24 GB
- Xet hash:
- 6c04509e521d28ead1efe47ccbda3d1d30d2d1122896be528e0c55fc20329699
- Size of remote file:
- 2.24 GB
- SHA256:
- 370e2fefd6b0601022f45de55bbb4ae344cacb0692f588f0892d8a42f165827f
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