Table Question Answering
Transformers
PyTorch
Safetensors
English
bart
text2text-generation
multitabqa
multi-table-question-answering
Instructions to use vaishali/multitabqa-base-sql with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vaishali/multitabqa-base-sql with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("table-question-answering", model="vaishali/multitabqa-base-sql")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("vaishali/multitabqa-base-sql") model = AutoModelForSeq2SeqLM.from_pretrained("vaishali/multitabqa-base-sql") - Notebooks
- Google Colab
- Kaggle
Commit ·
04dc99e
1
Parent(s): 6627f2e
Adding `safetensors` variant of this model (#1)
Browse files- Adding `safetensors` variant of this model (c6ecf5d7995ba3e6840ef179bad21168faa4663c)
Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:791d1876f837d83963c7c00586d835b1f979165fcc9cd012dca9d7606a26b083
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size 557912620
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