Instructions to use google/tapas-large-finetuned-wtq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/tapas-large-finetuned-wtq with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("table-question-answering", model="google/tapas-large-finetuned-wtq")# Load model directly from transformers import AutoTokenizer, AutoModelForTableQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("google/tapas-large-finetuned-wtq") model = AutoModelForTableQuestionAnswering.from_pretrained("google/tapas-large-finetuned-wtq", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 647136cf37af5e8b27b37a6589a4f3cef81dfaa2f31da7caff1e788604831491
- Size of remote file:
- 1.35 GB
- SHA256:
- fba128c471534dfe9a81e78f332ccc9f091ee62a3a52e46b81643c13ff94b95e
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