Instructions to use RAPIDS/distilbert-cyberlogs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RAPIDS/distilbert-cyberlogs with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("RAPIDS/distilbert-cyberlogs", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from RAPIDS/distilbert-cyberlogs: direct link, hf CLI and curl.
- Browser
- Download file 263 MB
-
https://huggingface.co/RAPIDS/distilbert-cyberlogs/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://RAPIDS/distilbert-cyberlogs/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/RAPIDS/distilbert-cyberlogs/resolve/main/pytorch_model.bin
263 MB
- Xet hash:
- 8d259cbb8f8a4cf77647835d6659187d81fdbb5c16228e7cb92c356eeb01e273
- Size of remote file:
- 263 MB
- SHA256:
- 89bb1c03c52a90f666a7ef6b216c5fa07608ce4355b16dc984192f1edb08b113
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