Instructions to use google/tapas-base-finetuned-tabfact with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/tapas-base-finetuned-tabfact with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="google/tapas-base-finetuned-tabfact")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("google/tapas-base-finetuned-tabfact") model = AutoModelForSequenceClassification.from_pretrained("google/tapas-base-finetuned-tabfact", device_map="auto") - Notebooks
- Google Colab
- Kaggle
TF model weights
Browse files- tf_model.h5 +3 -0
tf_model.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:26ac1990fa8365d8f822d926a961e96cd33929fc409592265d16e5fc201ad841
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size 442992576
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