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:
- c0685dba77cf80e75a18e9b42277b0d49580d3b26f3d6cff1665df2e5aa4efea
- Size of remote file:
- 876 MB
- SHA256:
- 85457631b5da9b23a1675eaeffc44f5facefad5297600a37e57cbde50f96b633
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