Instructions to use microsoft/tapex-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/tapex-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("table-question-answering", model="microsoft/tapex-large")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("microsoft/tapex-large") model = AutoModelForSeq2SeqLM.from_pretrained("microsoft/tapex-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 50b0c1c38f045a72c9bf4b92786c509fc144dd7dd95d7c10f8778a3768fe9abb
- Size of remote file:
- 1.63 GB
- SHA256:
- 67d1d5900b9b743144aeb01ef42d86b98b45b0ac2863b7eef721de8eb7b1e8f7
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