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Entropix, a novel sampling strategy, has sparked a debate within the research community regarding its approach and efficacy. Critics from the academic sphere have expressed skepticism, attributing the backlash to cultural differences rather than any fraudulent activity. Supporters argue that Entropix represents a shift in how research is conducted, emphasizing open experimentation and transparency. Recent evaluations by the authors indicate that Entropix achieved a 20% relative improvement on the GPQA zero-shot benchmark using the Qwen 2.5 500m model. However, the method's reliance on string matching for evaluations has raised questions about compatibility with existing evaluation frameworks.
Official entropix evals from the authors. A 20% relative improvement on GPQA zero-shot is insane! Notes: - Qwen 2.5 500m was used here - You cannot evaluate on the logprobs because entropix is a sampler - You need string matching for evals (incompatible with lm_eval) https://t.co/DAG5COGPyl
This is a banger post that is spot on. Entropix is like the antidote to how academics work. They just ship and keep experimenting openly, not promising anything but showing exciting examples of what it can enable https://t.co/CbErZnnr8L
This and @_xjdr responses (https://t.co/0Z7BU9nf7s), I think, excellently address community skepticism about entropix (as a comprehensive research program. If you wanted a production grade model agnostic sampler to ship with your llama.cpp wrapper, well yeah, not today buddy) https://t.co/5pUkW6vQxu
