Instructions to use google/tapas-small-finetuned-wtq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/tapas-small-finetuned-wtq with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("table-question-answering", model="google/tapas-small-finetuned-wtq")# Load model directly from transformers import AutoTokenizer, AutoModelForTableQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("google/tapas-small-finetuned-wtq") model = AutoModelForTableQuestionAnswering.from_pretrained("google/tapas-small-finetuned-wtq", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 33a5a947e2426a3c8fbeb78c71772b2cf70f492b7991ce7831b3f6222cad605c
- Size of remote file:
- 117 MB
- SHA256:
- ef38fe0495f994aa4487310f2087dbd0e79fb4642d31e8d76f6db0a1a6ee12f6
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