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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d05ea223454d9977c1c3b6c8d52238951e98191a17e1064faffdea6632801bdc
- Size of remote file:
- 45.9 MB
- SHA256:
- d6eb9d3a7b831ecbb31b42dcd0799d4c70f0bc96609d0c7cb585ace00d5bc555
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