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:
- 60297627a294bb913359c5f0fa3a6509a21ba7e71147da199b182f81b9741ecb
- Size of remote file:
- 45.8 MB
- SHA256:
- fc6aa6a34c5b6e5ed5d9392d7f3424acd591862e1b468b7b79bd864a2f0bb5c5
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