RemySkye/Gemma-4-E2B-it-qat-abliterated-UD-Q4_K_XL-GGUF overview
Huihui Gemma 4 E2B QAT — UD Q4 K XL like Source: huihui ai/Huihui gemma 4 E2B it qat q4 0 unquantized abliterated Files Huihui gemma 4 E2B it qat UD Q4 K XL li…
Runs locally from ~941.1 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
Model Details
Model README
---
license: apache-2.0
base_model:
- huihui-ai/Huihui-gemma-4-E2B-it-qat-q4_0-unquantized-abliterated
tags:
- gguf
- gemma4
- qat
- q4_0
- abliterated
- uncensored
- llama.cpp
---
Huihui Gemma 4 E2B QAT — UD-Q4_K_XL-like
Source:
huihui-ai/Huihui-gemma-4-E2B-it-qat-q4_0-unquantized-abliterated
Files
Huihui-gemma-4-E2B-it-qat-UD-Q4_K_XL-like.gguf— main modelmmproj-BF16.gguf— BF16 multimodal projectorimatrix_unsloth.gguf_file— exact Unsloth importance matrix usedquantization_manifest.json— hashes and provenance
Conversion
- llama.cpp commit:
fc6545d322a9ea6643f77439b31b66f403ba2cad - Main quant type:
Q4_0 --pure: enabled- imatrix:
unsloth/gemma-4-E2B-it-GGUF/imatrix_unsloth.gguf_file - mmproj:
unsloth/gemma-4-E2B-it-qat-GGUF/mmproj-BF16.gguf
Important distinction
This is a publicly reproducible Unsloth-like QAT conversion, not the
official Unsloth UD-Q4_K_XL algorithm.
Unsloth's official Gemma 4 QAT GGUFs use additional scale/lattice recovery
logic when mapping the BF16 QAT lattice into llama.cpp's Q4_0 representation.
That exact recovery procedure is not exposed as a standard public
llama-quantize option.
llama.cpp example
llama-server \
-m Huihui-gemma-4-E2B-it-qat-UD-Q4_K_XL-like.gguf \
--mmproj mmproj-BF16.gguf \
--jinja \
-ngl 999Run RemySkye/Gemma-4-E2B-it-qat-abliterated-UD-Q4_K_XL-GGUF with guIDE
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