|
|
--- |
|
|
language: en |
|
|
license: mit |
|
|
tags: |
|
|
- text-classification |
|
|
- transformers |
|
|
- legal |
|
|
- pdf |
|
|
datasets: |
|
|
- custom |
|
|
model-index: |
|
|
- name: legal_document_classifier |
|
|
results: [] |
|
|
--- |
|
|
|
|
|
# Legal Document Classifier |
|
|
|
|
|
This is a fine-tuned BERT-based model for classifying legal documents into contract, amendment, or other. |
|
|
|
|
|
## Usage |
|
|
|
|
|
```python |
|
|
from transformers import AutoTokenizer, AutoModelForSequenceClassification |
|
|
|
|
|
model = AutoModelForSequenceClassification.from_pretrained("karthikvarunn/legal_document_classifier") |
|
|
tokenizer = AutoTokenizer.from_pretrained("karthikvarunn/legal_document_classifier") |
|
|
|
|
|
inputs = tokenizer("Your document text here...", return_tensors="pt") |
|
|
outputs = model(**inputs) |
|
|
|
