Instructions to use google/tapas-tiny-finetuned-wtq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/tapas-tiny-finetuned-wtq with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("table-question-answering", model="google/tapas-tiny-finetuned-wtq")# Load model directly from transformers import AutoTokenizer, AutoModelForTableQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("google/tapas-tiny-finetuned-wtq") model = AutoModelForTableQuestionAnswering.from_pretrained("google/tapas-tiny-finetuned-wtq") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8dabaa0ff2d05b38e7547b584b975ee50b0baf6df618d158c596e5822e673745
- Size of remote file:
- 18.1 MB
- SHA256:
- 7db991e3ea8a344b8df2c33f77ad6593fd40d66f0cce0a7899374d6725be5f98
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