Instructions to use nlpaueb/legal-bert-base-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nlpaueb/legal-bert-base-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="nlpaueb/legal-bert-base-uncased")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("nlpaueb/legal-bert-base-uncased") model = AutoModelForPreTraining.from_pretrained("nlpaueb/legal-bert-base-uncased", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from nlpaueb/legal-bert-base-uncased: direct link, hf CLI and curl.
- Browser
- Download file 440 MB
-
https://huggingface.co/nlpaueb/legal-bert-base-uncased/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://nlpaueb/legal-bert-base-uncased/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/nlpaueb/legal-bert-base-uncased/resolve/main/flax_model.msgpack
440 MB
- Xet hash:
- 7e28741e09575847760e853364740fab5c668175f7f04f63b1233e7792475750
- Size of remote file:
- 440 MB
- SHA256:
- 89fc19b120310549ed04f4810f6fd9a2c782f08383ccd2b7cf2df150518a1de8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.