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noisebridge
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Model Details
Model Provider
noisebridge
Model Tree
Qwen/Qwen3.8-27B
Input Modalities
Output Modalities
Supported Functionality
| Path | What it is |
|---|---|
qwen3.8-27b-taiwan-pilled-UD-Q4_K_M.gguf | 4-bit GGUF, Unsloth Dynamic Q4_K_M profile — the same per-tensor quantization recipe as unsloth/Qwen3.8-27B-GGUF, reproduced using their published imatrix_unsloth.gguf and per-tensor type map. Drop-in replacement for Qwen3.8-27B-UD-Q4_K_M.gguf. |
LoRA/ | The LoRA adapter (rank 16), PEFT-compatible |
| Root files | Merged bf16 checkpoint (full model, transformers/safetensors) |
Vision and MTP are unchanged from the base model — the LoRA only touched the language model's linear layers. This repo intentionally ships no mmproj or MTP files: your existing Qwen3.8-27B vision projector (e.g. 8-bit mmproj) and MTP module GGUFs from the base model's quant repos work with this model as-is.
Same as base Qwen3.8-27B:
temperature=1.0, top_p=0.95, top_k=20, min_p=0.0temperature=0.7, top_p=0.80, top_k=20, min_p=0.0, presence_penalty=1.5bash
llama-server -m qwen3.8-27b-taiwan-pilled-UD-Q4_K_M.gguf --ctx-size 32768The GGUF replicates the Unsloth Dynamic Q4_K_M profile exactly:
convert_hf_to_ggufllama-quantize --imatrix imatrix_unsloth.gguf --tensor-type-file <map> where the map is the per-tensor quantization table extracted from unsloth's published Qwen3.8-27B-UD-Q4_K_M.gguf (Q4_K/Q5_K/Q6_K/IQ4_XS/Q8_0 mix + F32 linear-attention state weights)Apache 2.0 (see LICENSE), inheriting from the Apache-2.0 Qwen3.8-27B base. The training corpus is licensed separately (CC BY-SA 4.0) at its own repo.