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Llm-leaderboard Alternatives
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
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matrix-factorization
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llm-leaderboard reviews and mentions
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Email Obfuscation Rendered Almost Ineffective Against ChatGPT
This is assuming you’re using a really big LLM behind a paid service. There are plenty of smaller open source models. Not sure at what point it’s not “large” but when fine tuned they are capable of matching the largest LLM in performance on narrow tasks.
Some of these open source models can even be run on your local machine. It’d be very inexpensive to run thousands of pages through it.
https://llm-leaderboard.streamlit.app/
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Is the ChatGPT and Bing AI boom already over?
palm-2-l-instruct scores 0.909 on Winogrande few-shot.
https://github.com/LudwigStumpp/llm-leaderboard/blob/main/RE...
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Meta is preparing to launch a new open source coding model, dubbed Code Llama, that may release as soon as next week
They said it "rivals OpenAI’s Codex model" which performs worse than starcoder-16b on HumanEval-Python (pass@1) according to https://github.com/LudwigStumpp/llm-leaderboard
- All Model Leaderboards (that I know)
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GPT-3.5 and GPT-4 performance in Open LLM Leaderboard tests?
Yes, see this leaderboard for a comparison: https://llm-leaderboard.streamlit.app/
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Sharing my comparison methodology for LLM models
So I've tried to use a basic matrix factorization method to estimate unknown benchmark scores for models based on the known benchmark scores. Basically, I assume each model has some intrinsic "quality" score, and the known benchmarks are assumed to be a linear function of the quality score. This is similar to matrix factorization with only 1 latent factor (though the bias values have to handled differently). Then I fit the known benchmark scores from https://github.com/LudwigStumpp/llm-leaderboard to my parameters, and estimate the remaining benchmark scores.
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A note from our sponsor - SaaSHub
www.saashub.com | 2 May 2024
Stats
LudwigStumpp/llm-leaderboard is an open source project licensed under Apache License 2.0 which is an OSI approved license.
The primary programming language of llm-leaderboard is Python.
Popular Comparisons
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