Instructions to use hf-internal-testing/tiny-random-TapasForQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-TapasForQuestionAnswering with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("table-question-answering", model="hf-internal-testing/tiny-random-TapasForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForTableQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-TapasForQuestionAnswering") model = AutoModelForTableQuestionAnswering.from_pretrained("hf-internal-testing/tiny-random-TapasForQuestionAnswering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8c6d16d9bc7d4b4d264d375f45aa8cd902e65e1801936570af5535f5cd3fde6c
- Size of remote file:
- 4.28 MB
- SHA256:
- e9aebf4eae6735ba4958b64caf5a5e5f5a63ab66cb0feef70b29fd3c398ec9c5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.