Table Question Answering
Transformers
PyTorch
Safetensors
English
bart
text2text-generation
multitabqa
multi-table-question-answering
Instructions to use vaishali/multitabqa-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vaishali/multitabqa-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("table-question-answering", model="vaishali/multitabqa-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("vaishali/multitabqa-base") model = AutoModelForSeq2SeqLM.from_pretrained("vaishali/multitabqa-base") - Notebooks
- Google Colab
- Kaggle
Commit ·
cb7590b
1
Parent(s): 6ccde1d
Adding `safetensors` variant of this model (#1)
Browse files- Adding `safetensors` variant of this model (ad060941fc45ef7f57e234f09df35841cb0aa06a)
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 sha256:4fa33c77f936e52cc9de06eb8c1daed37635b6552840bd0ed8d3c77fcfb10546
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size 557912620
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