Instructions to use microsoft/tapex-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/tapex-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("table-question-answering", model="microsoft/tapex-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("microsoft/tapex-base") model = AutoModelForSeq2SeqLM.from_pretrained("microsoft/tapex-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from microsoft/tapex-base: direct link, hf CLI and curl.
- Browser
- Download file 558 MB
-
https://huggingface.co/microsoft/tapex-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://microsoft/tapex-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/microsoft/tapex-base/resolve/main/pytorch_model.bin
558 MB
- Xet hash:
- e6c0759ed747846b8f31f88a438146c8bf2fa6b08e30aec885d6a2409edb6c41
- Size of remote file:
- 558 MB
- SHA256:
- a5ad9ccefcb7e2df3b2c2e655c4d673e53b27ec8d8e1a57b2152865fe9c1de5d
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