Instructions to use ylu610/FT-T5-3B-Verifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ylu610/FT-T5-3B-Verifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ylu610/FT-T5-3B-Verifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ylu610/FT-T5-3B-Verifier") model = AutoModelForSeq2SeqLM.from_pretrained("ylu610/FT-T5-3B-Verifier") - Notebooks
- Google Colab
- Kaggle
Improve model card with metadata, code example and links
#1
by nielsr HF Staff - opened
This PR improves the model card by adding essential metadata (pipeline_tag, library_name), a clear usage example with the transformers library, and links to the paper and GitHub repository. The pipeline tag is set to text-classification given the model's role in claim verification.
ylu610 changed pull request status to closed