Text Classification
Transformers
Safetensors
English
longformer
legal
document-classification
multi-class-classification
msme
dispute-resolution
indian-legal
Instructions to use abhinavdread/msme-legal-dispute-classifier-longformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abhinavdread/msme-legal-dispute-classifier-longformer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="abhinavdread/msme-legal-dispute-classifier-longformer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("abhinavdread/msme-legal-dispute-classifier-longformer") model = AutoModelForSequenceClassification.from_pretrained("abhinavdread/msme-legal-dispute-classifier-longformer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 388592b525870e3eea9e791aac30bc7b47dceeaf77bd5018024c807edf2a9e22
- Size of remote file:
- 5.2 kB
- SHA256:
- 7a66b75993cd971181b90f30bc3d6bdfdb7bab15f5029293b662d494f20fff02
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