Instructions to use andrejmiscic/simcls-scorer-billsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use andrejmiscic/simcls-scorer-billsum with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="andrejmiscic/simcls-scorer-billsum")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("andrejmiscic/simcls-scorer-billsum") model = AutoModel.from_pretrained("andrejmiscic/simcls-scorer-billsum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d75a1e4c34811492999d34060b76e2abbe350790a568d2acede533c8cb4a8eef
- Size of remote file:
- 499 MB
- SHA256:
- c17490a0fbc2783f5b67942785a5745cc24cb9d5cad7346eb8c2b5f33194315e
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