Instructions to use PrimeQA/tapas-based-tableqa-wikisql-lookup with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PrimeQA/tapas-based-tableqa-wikisql-lookup with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("table-question-answering", model="PrimeQA/tapas-based-tableqa-wikisql-lookup")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTableQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("PrimeQA/tapas-based-tableqa-wikisql-lookup") model = AutoModelForTableQuestionAnswering.from_pretrained("PrimeQA/tapas-based-tableqa-wikisql-lookup", 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.2c98136
-
Update README.md
6fdf829 -
Update README.md
8aa5a1d
-
uploaded PyTorch model bin
fc5668b -
uploaded vocabulary
b7759fb -
uploaded training_args.json
df01f48 -
uploaded tokeniser_config.json
163b78a -
uploaded special tokens map
dfd763f
-
Uploaded config.json
d94e5b7 -
initial commit
fecc1a2