WikiSQL
hanakotoba
WikiSQL | hanakotoba | |
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2 | 1 | |
1,566 | 1 | |
1.7% | - | |
0.0 | 3.3 | |
10 months ago | 5 months ago | |
HTML | HTML | |
BSD 3-clause "New" or "Revised" License | - |
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WikiSQL
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List of code generation datasets (open source)
WikiSQL
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Anyone else witnessing a panic inside NLP orgs of big tech companies?
Natural language processing/understanding/generation is solved (at least in English).
LLMs produce perfectly fluent output and can understand natural language input as well as any human.
However knowledge representation is not solved. We still don't know how to interface a perfect LLM to other systems in the same way a human does things like looking up facts we aren't confident of or using a calculator to do math we cant' do in our head.
These are very significant problems and super important. But they are more adjacent to NLP in the same way tasks like something like Text-to-SQL [1] isn't a pure NLP task.
[1] for example https://github.com/salesforce/WikiSQL
hanakotoba
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Evidence – Business Intelligence as Code
Thanks for sharing, that looks great! That Datapane example is more a hello world web app that runs Python code in the backend (so requires a backend server - Fly.io in this example).
An example of a standalone report would be something like this, from one of our users: https://cloud.datapane.com/reports/dkjbvwk/literature-in-blo... (code: https://github.com/ryancahildebrandt/hanakotoba) or https://cloud.datapane.com/reports/aAMaqoA/when-fact-is-fals...
What are some alternatives?
ASH-IR-Dataset - An impulse response dataset for binaural synthesis of spatial audio systems on headphones
evidence - Business intelligence as code: build fast, interactive data visualizations in pure SQL and markdown
news - JSON News Service
notebook
jupysql - Better SQL in Jupyter. 📊
datapane - Build and share data reports in 100% Python
nba-monte-carlo - Monte Carlo simulation of the NBA season, leveraging dbt, duckdb and evidence.dev