Instructions to use opticalmaterials/opticaltable_sqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use opticalmaterials/opticaltable_sqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("table-question-answering", model="opticalmaterials/opticaltable_sqa")# Load model directly from transformers import AutoTokenizer, AutoModelForTableQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("opticalmaterials/opticaltable_sqa") model = AutoModelForTableQuestionAnswering.from_pretrained("opticalmaterials/opticaltable_sqa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4908eba5d0afc705e10400627462e2f142e7c7f2d5844a15c952f9a8725f70fb
- Size of remote file:
- 443 MB
- SHA256:
- b088c9a18e01732ec46816913973ba3ebdc3784ed52eddb6d1c77cf80d3bc71e
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