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:
- c0339c46400a95e137e6b8d1d5e9b367cd6a828189e679b7298ff1dfc5b5216b
- Size of remote file:
- 18.2 MB
- SHA256:
- c8cae0581b4c90bafb8ef5004a333d062deb384aa7ea4d4c21c919d8a00e8810
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