Instructions to use google/tapas-tiny-finetuned-sqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/tapas-tiny-finetuned-sqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("table-question-answering", model="google/tapas-tiny-finetuned-sqa")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTableQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("google/tapas-tiny-finetuned-sqa") model = AutoModelForTableQuestionAnswering.from_pretrained("google/tapas-tiny-finetuned-sqa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from google/tapas-tiny-finetuned-sqa: direct link, hf CLI and curl.
- Browser
- Download file 18.2 MB
-
https://huggingface.co/google/tapas-tiny-finetuned-sqa/resolve/main/tf_model.h5
- Command line
-
hf download hf://google/tapas-tiny-finetuned-sqa/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/google/tapas-tiny-finetuned-sqa/resolve/main/tf_model.h5
18.2 MB
- Xet hash:
- 9050c515d8577714af36ba1c6191d1e001ec3d8548f508afede7624680af76e8
- Size of remote file:
- 18.2 MB
- SHA256:
- f2599db9036f19bd46c47e76b4cfd969f9801e0db1114f858ee6f39a9edf0479
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