Instructions to use google/tapas-large-finetuned-sqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/tapas-large-finetuned-sqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("table-question-answering", model="google/tapas-large-finetuned-sqa")# Load model directly from transformers import AutoTokenizer, AutoModelForTableQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("google/tapas-large-finetuned-sqa") model = AutoModelForTableQuestionAnswering.from_pretrained("google/tapas-large-finetuned-sqa") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5850c954d53b37fa94b26a2f660a0bb9cf96b6504028d10bb3ac73f1c462dafe
- Size of remote file:
- 1.35 GB
- SHA256:
- ef1175c24b74689841c9dda73e032eb38a3ef15e1368d02a407ca9d854b515fd
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