Instructions to use google/tapas-medium-finetuned-wtq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/tapas-medium-finetuned-wtq with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("table-question-answering", model="google/tapas-medium-finetuned-wtq")# Load model directly from transformers import AutoTokenizer, AutoModelForTableQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("google/tapas-medium-finetuned-wtq") model = AutoModelForTableQuestionAnswering.from_pretrained("google/tapas-medium-finetuned-wtq") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c3b498b39d95f57736e6cd28aa7b2c795029b92a10ef2ee0c8628355b70c1170
- Size of remote file:
- 168 MB
- SHA256:
- 800535267c5f94b4616bdb783da7aaac80ee2d929a2a8aded188bfcaf0de31b9
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