Instructions to use microsoft/tapex-base-finetuned-wtq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/tapex-base-finetuned-wtq with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("table-question-answering", model="microsoft/tapex-base-finetuned-wtq")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("microsoft/tapex-base-finetuned-wtq") model = AutoModelForSeq2SeqLM.from_pretrained("microsoft/tapex-base-finetuned-wtq", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from microsoft/tapex-base-finetuned-wtq: direct link, hf CLI and curl.
- Browser
- Download file 558 MB
-
https://huggingface.co/microsoft/tapex-base-finetuned-wtq/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://microsoft/tapex-base-finetuned-wtq/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/microsoft/tapex-base-finetuned-wtq/resolve/main/pytorch_model.bin
558 MB
- Xet hash:
- 61d188471e149cf4712c7acdfcefdef7d281a751016e813ec7a88f4ddbdb2dba
- Size of remote file:
- 558 MB
- SHA256:
- 03f113787ca0b5af5741b1e14f23c4f087c8e7dc038558db4fbf74b9804a4e9f
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