google/tapas-large-finetuned-wtq
google/tapas-large-finetuned-wtq is a table question answering model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.
What to verify before deployment
- Confirm the exact weight format and quantization.
- Measure memory at your intended context or image size.
- Review model-card limitations and evaluation methodology.
- Test latency and throughput on your target runtime.
Likely commercial-friendly
License metadata is an index signal, not legal advice. Follow the repository license and any model-specific acceptable-use terms.
Verify at the source →More table-question-answering models
google/tapas-base-finetuned-wtq
google/tapas-base-finetuned-wtq is a table question answering model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.
google/tapas-large-finetuned-wtq
google/tapas-large-finetuned-wtq is a table question answering model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.
microsoft/tapex-large
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microsoft/tapex-base-finetuned-wikisql
microsoft/tapex-base-finetuned-wikisql is a table question answering model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.
microsoft/tapex-large-finetuned-wtq
microsoft/tapex-large-finetuned-wtq is a table question answering model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.
microsoft/tapex-base-finetuned-wtq
microsoft/tapex-base-finetuned-wtq is a table question answering model indexed for deployment research. Estimated minimum GPU memory is 8 GB. It is publicly listed on Hugging Face.
Operate a GPU cloud or inference API?
Reach developers after they have selected a model and are ready to run it.