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", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f639d088d9d01f1a140bb69ddb419c5b3adc0f47a4311d403eeff0b05f3b0468
- Size of remote file:
- 1.35 GB
- SHA256:
- 606243550ac7bd22bfdada468bb63b0caf78f6fd7fc76cffb343851330a6476f
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