Instructions to use AI4Sec/cyner-xlm-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AI4Sec/cyner-xlm-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="AI4Sec/cyner-xlm-roberta-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("AI4Sec/cyner-xlm-roberta-base") model = AutoModelForTokenClassification.from_pretrained("AI4Sec/cyner-xlm-roberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from AI4Sec/cyner-xlm-roberta-base: direct link, hf CLI and curl.
- Browser
- Download file 1.11 GB
-
https://huggingface.co/AI4Sec/cyner-xlm-roberta-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://AI4Sec/cyner-xlm-roberta-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/AI4Sec/cyner-xlm-roberta-base/resolve/main/pytorch_model.bin
1.11 GB
- Xet hash:
- 4e7354eca2640dd64976645d55e01834499d60913a60b44272625681a102b31f
- Size of remote file:
- 1.11 GB
- SHA256:
- 3459be1f3c712f4f0cc58b4df47d51203afee3a3cbea4340df7dc307932e126f
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