Instructions to use avichr/Legal-heBERT_ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use avichr/Legal-heBERT_ft with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="avichr/Legal-heBERT_ft")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("avichr/Legal-heBERT_ft") model = AutoModelForMaskedLM.from_pretrained("avichr/Legal-heBERT_ft", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9bef8314ff85e42f731b5890d10550b5fac700a30955cccc097d000bee745592
- Size of remote file:
- 438 MB
- SHA256:
- 8fe0ee799b3d916bd7980324e49819f3ca676714c495f2be75e95af407a119e8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.