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:
- ba68a52a3686045f7115312fd5bb8a64b735c0cf51a489109c354b67786d094e
- Size of remote file:
- 1.35 GB
- SHA256:
- 4f09013d3fd426124979b0d5b07d9ac02c5421d095b98536112722f9cdd61c90
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