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:
- 78949c3e680bfbb9d18122b2f6e47513e784c8cd0e7d9b32fc2e043beaa1d12e
- Size of remote file:
- 4.92 kB
- SHA256:
- 1d67f433b74e0c5015495d7470ff35e34ab20bb7abc2e1887dfc6d557fdf2970
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