Instructions to use artefactory/BERTJudge-Formatted-QCR-OOD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use artefactory/BERTJudge-Formatted-QCR-OOD with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="artefactory/BERTJudge-Formatted-QCR-OOD", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("artefactory/BERTJudge-Formatted-QCR-OOD", trust_remote_code=True) model = AutoModelForSequenceClassification.from_pretrained("artefactory/BERTJudge-Formatted-QCR-OOD", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
Add pipeline tag and library name
#1
by nielsr HF Staff - opened
Hi, I'm Niels from the community science team at Hugging Face.
This PR improves the model card by adding relevant metadata:
pipeline_tag: text-classification: This ensures the model is correctly indexed and discoverable on the Hub.library_name: transformers: Since the model is compatible with the Transformers library (as seen in theconfig.jsonand its architecture), this tag enables automated code snippets and the "Use in Transformers" button.
hgissbkh changed pull request status to closed
hgissbkh deleted the
refs/pr/1 ref