chains/benchmarks, other LLMs #30
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…suite of big bench
saulpw
reviewed
Jun 10, 2023
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I ended up writing a few more ops for this PR, some of which seem obvious (!csv-parse) and some of which I expect will change (the !metrics- ones). I'm especially interested in getting the changes to llm.py merged so we have a way of calling LLMs from different sources |
saulpw
reviewed
Jun 12, 2023
| s = 'model,task\n' + "\n".join([model+","+task for model in models for task in tasks]) | ||
| with open('model-task.csv', 'w') as f: | ||
| f.write(s) | ||
| !csv-parse model-task.csv |
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This whole block is clever, but we should figure out how a !cross or something should work.
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totally, if you're doing that separately then we can hold this PR off until that's merged
dovinmu
commented
Jun 12, 2023
| !format | ||
| https://raw.githubusercontent.com/google/BIG-bench/main/bigbench/benchmark_tasks/{task}/task.json | ||
| !fetch-url | ||
| # name=name description=description |
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The problem with this not working is that we can't automatically construct good prompts from the JSON file, since it has context for what the LLM is actually classifying
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(closing #28 in favor of this)
At minimum before we merge this branch:
for the binary classification script:
these are nice to haves, basically they'd make it so we were using the bigbench tasks more as intended:
If #27 is resolved then we could compute multiple accuracy metrics. And we could also optionally explore having another script that runs the entire slate of tasks on a set of models.