Text Classification
Transformers
Safetensors
English
modernbert
litil-labs
legal
clause-classification
ledgar
text-embeddings-inference
Instructions to use litillabs/litil-clause-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use litillabs/litil-clause-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="litillabs/litil-clause-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("litillabs/litil-clause-classifier") model = AutoModelForSequenceClassification.from_pretrained("litillabs/litil-clause-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download example_input.json from litillabs/litil-clause-classifier: direct link, hf CLI and curl.
- Browser
- Download file 203 Bytes
-
https://huggingface.co/litillabs/litil-clause-classifier/resolve/main/example_input.json
- Command line
-
hf download hf://litillabs/litil-clause-classifier/example_input.json
-
curl -L -o example_input.json https://huggingface.co/litillabs/litil-clause-classifier/resolve/main/example_input.json
203 Bytes
| { | |
| "text": "The receiving party shall keep all confidential information secret and shall not disclose it to any third party without the disclosing party's prior written consent.", | |
| "text_pair": null | |
| } | |