Text Classification
Transformers
Safetensors
English
bert
legal
sequence-classification
indian-law
text-embeddings-inference
Instructions to use negi2725/LegalBertNew with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use negi2725/LegalBertNew with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="negi2725/LegalBertNew")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("negi2725/LegalBertNew") model = AutoModelForSequenceClassification.from_pretrained("negi2725/LegalBertNew", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from negi2725/LegalBertNew: direct link, hf CLI and curl.
- Browser
- Download file 702 kB
-
https://huggingface.co/negi2725/LegalBertNew/resolve/main/tokenizer.json
- Command line
-
hf download hf://negi2725/LegalBertNew/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/negi2725/LegalBertNew/resolve/main/tokenizer.json
702 kB
File too large to display, you can check the raw version instead.