Instructions to use google/tapas-mini-finetuned-wtq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/tapas-mini-finetuned-wtq with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("table-question-answering", model="google/tapas-mini-finetuned-wtq")# Load model directly from transformers import AutoTokenizer, AutoModelForTableQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("google/tapas-mini-finetuned-wtq") model = AutoModelForTableQuestionAnswering.from_pretrained("google/tapas-mini-finetuned-wtq") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ec13140232ecf18357bf06ca7c19aa07f3569fbc01ed31c5c118bc6734d7a645
- Size of remote file:
- 45.8 MB
- SHA256:
- c41636b821f295462ab9ab9b21cbb5a5f810e6017318684b0de5bfce46aac5c3
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