Instructions to use google/tapas-medium-finetuned-tabfact with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/tapas-medium-finetuned-tabfact with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="google/tapas-medium-finetuned-tabfact")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("google/tapas-medium-finetuned-tabfact") model = AutoModelForSequenceClassification.from_pretrained("google/tapas-medium-finetuned-tabfact") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 66a312972b43185c42d8ec47ded026460e95bc1fee1e1dae15f5d657e57ed5d4
- Size of remote file:
- 168 MB
- SHA256:
- 795d9d42056d52296b2aff5045b5e22f8d073267d316abd50940be67fae2d628
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