Instructions to use snu-aidas/MATA_confidence_checker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use snu-aidas/MATA_confidence_checker with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="snu-aidas/MATA_confidence_checker")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("snu-aidas/MATA_confidence_checker") model = AutoModelForSequenceClassification.from_pretrained("snu-aidas/MATA_confidence_checker", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Add model card for MATA Confidence Checker
#1
by nielsr HF Staff - opened
This PR updates the model card for the MATA confidence checker. It replaces the default template with specific details about its role within the MATA framework. Key changes include:
- Adding the
table-question-answeringpipeline tag. - Linking to the paper MATA: Multi-Agent Framework for Reliable and Flexible Table Question Answering.
- Linking to the official GitHub repository.
- Describing the model's architecture, specific tokens, and purpose within the multi-agent TableQA framework.