Token Classification
Transformers
Safetensors
leg-1.0-guardrail
feature-extraction
custom-code
safety
deberta-v2
sequence-classification
custom_code
Instructions to use clulab/LEG-1.0-aegis2.0-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use clulab/LEG-1.0-aegis2.0-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="clulab/LEG-1.0-aegis2.0-base", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("clulab/LEG-1.0-aegis2.0-base", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download spm.model from clulab/LEG-1.0-aegis2.0-base: direct link, hf CLI and curl.
- Browser
- Download file 2.46 MB
-
https://huggingface.co/clulab/LEG-1.0-aegis2.0-base/resolve/main/spm.model
- Command line
-
hf download hf://clulab/LEG-1.0-aegis2.0-base/spm.model
-
curl -L -o spm.model https://huggingface.co/clulab/LEG-1.0-aegis2.0-base/resolve/main/spm.model
2.46 MB
- Xet hash:
- 6bd079d8585fbcdbf47cb3a534f888b5aaa32b8994301f5c47573e6cf825d7da
- Size of remote file:
- 2.46 MB
- SHA256:
- c679fbf93643d19aab7ee10c0b99e460bdbc02fedf34b92b05af343b4af586fd
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