Table Question Answering
Transformers
PyTorch
Safetensors
English
bart
text2text-generation
multitabqa
multi-table-question-answering
Instructions to use vaishali/multitabqa-base-atis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vaishali/multitabqa-base-atis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("table-question-answering", model="vaishali/multitabqa-base-atis")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("vaishali/multitabqa-base-atis") model = AutoModelForSeq2SeqLM.from_pretrained("vaishali/multitabqa-base-atis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Adding `safetensors` variant of this model
This is an automated PR created with https://huggingface.co/spaces/safetensors/convert This new file is equivalent to `pytorch_model.bin` but safe in the sense that no arbitrary code can be put into it. These files also happen to load much faster than their pytorch counterpart: https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb The widgets on your model page will run using this model even if this is not merged making sure the file actually works. If you find any issues: please report here: https://huggingface.co/spaces/safetensors/convert/discussions Feel free to ignore this PR.538ddb9
-
Upload 7 files
4f98f0e -
Update README.md
c61dda2 -
initial commit
91deede