Muse-Glimmer-30B-Heretic-Uncensored-GGUF

模型介绍

This repository disseminates a comprehensive suite of 27 GGUF (GPT-Generated Unified Format) quantizations of **Muse-Glimmer-30B-Heretic-Uncensored**, an abliterated derivative of Meta's Muse-Glimmer-30B produced with Heretic v1.4.0 by darkc0de. The release spans a memory footprint of 6.53 GB (IQ1_S) to 55.73 GB (F16/BF16), thereby accommodating deployment across heterogeneous hardware, from CPU-only systems to 32 GB VRAM accelerators. All sub-4-bit quantizations were calibrated with an importance matrix (imatrix) to mitigate quality degradation. The fidelity of the Q4_K_S variant relative to the F16 reference is quantified via token-level perplexity on a fixed evaluation set. The model exhibits **zero refusals on adult/NSFW content**; this property was empirically verified. The quantization selection is derived from the model's architectural properties and the memory constraints of representative target hardware. The model employs **grouped-query attention with 2 KV heads**, which renders the KV cache exceptionally compact: - 52 layers × 2 KV heads × 128 head_dim = **52 KiB/token at FP16** - Q8_0 KV cache: **26 KiB/token** → 64K context ≈ 1.7 GB - Q4_0 KV cache: **13 KiB/token** → 64K context ≈ 0.85 GB

主要特点

特点摘要待依据来源补齐，不凭模型名称推断能力。

局限与注意事项

暂无足够来源支持具体缺点结论。请重点验证实际任务表现、时延、数据政策、许可与版本生命周期。

来源报价与费用分析

同一模型在不同渠道、地区和配置下可能采用不同价格。下表独立保留各渠道报价，不将渠道价格视为厂商官方统一价格。

公开评测与运行配置

暂无已采集的可核验公开评分。模型未上榜不代表能力较低。

常见问题

资料来源与可追溯记录

许可证：apache-2.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。