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") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 491427649586daf90639b9a53eae8ef3304e012320baa2c2122716cb5a47e9fa
- Size of remote file:
- 1.35 GB
- SHA256:
- 39c8f6f475ba5cc3f9a4a09d950d9d63a9f5b7f217d132a3069ad063914c2ad0
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