Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use xshubhamx/InLegalBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xshubhamx/InLegalBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="xshubhamx/InLegalBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("xshubhamx/InLegalBERT") model = AutoModelForSequenceClassification.from_pretrained("xshubhamx/InLegalBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b0aab829817a155704dc3155ca04b6f8e83681652c5f7c16119ddca7773b2f9d
- Size of remote file:
- 876 MB
- SHA256:
- e518f3c20986f5cfcdceb9f39daadd6854a0274373674b73bbf9b12c35266d0a
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