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:
- 245c679ed16f9d448013253ba73b642191cacdd3b038d6c3173261bf68562995
- Size of remote file:
- 45.8 MB
- SHA256:
- c3f32ad0f6f14d2c618a9937fc1dc2a4aead05b4522672877630c9e8b7ed549e
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