Instructions to use google/tapas-mini-finetuned-sqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/tapas-mini-finetuned-sqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("table-question-answering", model="google/tapas-mini-finetuned-sqa")# Load model directly from transformers import AutoTokenizer, AutoModelForTableQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("google/tapas-mini-finetuned-sqa") model = AutoModelForTableQuestionAnswering.from_pretrained("google/tapas-mini-finetuned-sqa") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9b538f6febbf3ef84aef9c90c749b985d91c93fb5a5b8d333d55d1cf1abed857
- Size of remote file:
- 45.8 MB
- SHA256:
- bf1592fc014019957427d3c752ed775e5db7847a72465c0196c915636f8944f7
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