Instructions to use sec-classification/securebert_ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sec-classification/securebert_ft with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, RobertaForAverageSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sec-classification/securebert_ft") model = RobertaForAverageSequenceClassification.from_pretrained("sec-classification/securebert_ft", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from sec-classification/securebert_ft: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/sec-classification/securebert_ft/resolve/main/model.safetensors
- Command line
-
hf download hf://sec-classification/securebert_ft/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/sec-classification/securebert_ft/resolve/main/model.safetensors
499 MB
- Xet hash:
- 6d34998947029d491edcb1f245e1ae12f03ba57f5cf05932e6b745e436efe465
- Size of remote file:
- 499 MB
- SHA256:
- 3cd7d15815ccb019f49f1aea7f8c276d67cf59e193444051dade57c4894238ad
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.