My benchmark for large language models
Date : 2024-02-19
Description
This summary was drafted with mixtral-8x7b-instruct-v0.1.Q5_K_M.gguf
This collection of tests is derived from real-life conversations he had with different LLMs. The benchmark includes tasks such as converting Python functions to equivalent but faster C functions, explaining the functionality of minified JavaScript, identifying data encoding formats, writing parsers from BNF-like grammars, converting English sentences to SQL queries, and writing bash one-liners. Carlini emphasizes the use of a simple dataflow domain-specific language (DSL) that facilitates adding new tests and realistically evaluating model capabilities.
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