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")# pip install -U transformers accelerate # 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", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
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README.md
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Disclaimer: The team releasing TAPAS did not write a model card for this model so this model card has been written by
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the Hugging Face team and contributors.
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# Results on SQA - Dev Accuracy
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Size | Reset | Dev Accuracy | Link
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Disclaimer: The team releasing TAPAS did not write a model card for this model so this model card has been written by
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the Hugging Face team and contributors.
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## Results on SQA - Dev Accuracy
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Size | Reset | Dev Accuracy | Link
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-------- | --------| -------- | ----
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