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:
- c1541bbd463c08d413c43727407974ca5f9a0b86621efc0767cca8a3f79f868a
- Size of remote file:
- 595 MB
- SHA256:
- dbe2e802a53e67d47f8047f4ed7f7d9e1e75934ab1bba6a10a296dc6024c030f
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