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A community proposal in r/LocalLLaMA urging members to stop fixating on tok/s speed metrics and instead create private quality benchmarks, especially to evaluate model quality across quantisation levels, and to share results with each other.
The article questions why Qwen hasn't released new small-scale models (1B/2B/4B), which affects accessibility and development for hardware-limited users, and mentions a similar issue with Google's Gemma series.
This paper examines covert dialect bias in large language models by analyzing their internal probability distributions across four English dialects, finding that models associate more negative housing-related adjectives with African American Vernacular English and Nigerian Pidgin, reflecting inherited biases similar to human discrimination.