AI正在发生 未来正在更新JEV-27B-VL-GGUF
GGUF builds of autotrust/JEV-27B-VL for llama.cpp's native decision endpoint `/v1/systemone`, with JEV's own readout: false/true for yes/no, the digits 0–5 for scores, and letters for choices, plus its decision-head bias and calibrated temperatures. These are also the builds for **older GPUs such as V100s**, which cannot run FP8/FP4 checkpoints. > **Requires a patched llama.cpp (for now).** The `jev` decision type is not in upstream llama.cpp yet. > Apply `llama.cpp-jev.patch` (made against upstream `bed0a85`) and build. It adds the converter class, > the GGUF metadata keys and the server readout. > ⚠️ **Q4_K_M is less accurate.** About 1 decision in 14 differs from full precision. Prefer Q8_0 when it > fits. Q4_K_M is for 24 GB-class cards.
译文尚未就绪，显示来源原文
GGUF builds of autotrust/JEV-27B-VL for llama.cpp's native decision endpoint `/v1/systemone`, with JEV's own readout: false/true for yes/no, the digits 0–5 for scores, and letters for choices, plus its decision-head bias and calibrated temperatures. These are also the builds for **older GPUs such as V100s**, which cannot run FP8/FP4 checkpoints. > **Requires a patched llama.cpp (for now).** The `jev` decision type is not in upstream llama.cpp yet. > Apply `llama.cpp-jev.patch` (made against upstream `bed0a85`) and build. It adds the converter class, > the GGUF metadata keys and the server readout. > ⚠️ **Q4_K_M is less accurate.** About 1 decision in 14 differs from full precision. Prefer Q8_0 when it > fits. Q4_K_M is for 24 GB-class cards.