CEDR generates reasoning solutions with continuous latent diffusion and a learned prompt encoder. This repository contains six selected-weight inference packages for GSM8K, MATH500, and coding, before and after NFT. The training and inference code and installation instructions are at chengxiang/CEDR. All use async clocks (2.5, 2, 1.5), CFG 1, batch size 32, and a 1,024-token diffusion canvas. The GSM8K post-NFT preset caps decoded responses at 767 tokens. Other presets use the canvas available after each prompt. See the code repository's evaluation guide for MATH500 and official HumanEval/MBPP base/plus scoring. Coding generation uses the combined 164 HumanEval and 378 MBPP tasks. Standard…
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Xiang Cheng
xc91
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Models on Hugging Face1
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