Instructions to use casehold/custom-legalbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use casehold/custom-legalbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="casehold/custom-legalbert")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("casehold/custom-legalbert", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from casehold/custom-legalbert: direct link, hf CLI and curl.
- Browser
- Download file 445 MB
-
https://huggingface.co/casehold/custom-legalbert/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://casehold/custom-legalbert/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/casehold/custom-legalbert/resolve/main/pytorch_model.bin
445 MB
- Xet hash:
- d71aee57b8aa6d747b25b91dbaf9e8767a1657a80b8e3eb528dc7c0af2d77ff0
- Size of remote file:
- 445 MB
- SHA256:
- 849fbb9481f0142223e379dc712f36184cb55ab6fd2be4361dbfb8df16b247bf
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