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AlexHung29629/gemma-4-E2B-it-abliteration-2-Q8_0-GGUF

AlexHung29629 Gemma GGUF second-order 131K ctx
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Abliteration classifier · v1.0.0
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Primary method

Unclassified

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Confidence
UNKNOWN
Why this label 1 signal
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  • no classification signals present (no abliterated, uncensored, or known producer/method markers)
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Downloads · lifetime
536
44 last 30d - cooling
Likes
0
Model age
4mo ago
created 2026-06-04
Downloads over time
Now550→from203↑171%
186319452585203 on Jun 10550 on Oct 11JunJulAugSepOct
Jun 10 → Oct 11 · 57 snapshots · spans 123 days

Genealogy 0 direct forks

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Metadata

Tags
gguf llama-cpp gguf-my-repo base_model:AlexHung29629/gemma-4-E2B-it-abliteration-2 base_model:quantized:AlexHung29629/gemma-4-E2B-it-abliteration-2 endpoints_compatible region:us

Related

Total size
4.63 GB
Files
4
Quantizations
2
Registered
2026-08-22 13:56
Last updated on HF
2026-06-04 08:44

Files by quantization

BF16 1 file 941 MB
mmproj-gemma-4-E2B-it-BF16.gguf 941 MB b23366be download
Auxiliary files 3 files 4.63 GB
gemma-4-e2b-it-abliteration-2-q8_0.gguf 4.63 GB 4f1450ca download
README.md 1.88 KB 0d33213d download
.gitattributes 1.62 KB d959e04e download

README current version from Hugging Face


base_model: AlexHung29629/gemma-4-E2B-it-abliteration-2
tags:

  • llama-cpp
  • gguf-my-repo

AlexHung29629/gemma-4-E2B-it-abliteration-2-Q8_0-GGUF

This model was converted to GGUF format from AlexHung29629/gemma-4-E2B-it-abliteration-2 using llama.cpp via the ggml.ai's GGUF-my-repo space.
Refer to the original model card for more details on the model.

Use with llama.cpp

Install llama.cpp through brew (works on Mac and Linux)

brew install llama.cpp

Invoke the llama.cpp server or the CLI.

CLI:

llama-cli --hf-repo AlexHung29629/gemma-4-E2B-it-abliteration-2-Q8_0-GGUF --hf-file gemma-4-e2b-it-abliteration-2-q8_0.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo AlexHung29629/gemma-4-E2B-it-abliteration-2-Q8_0-GGUF --hf-file gemma-4-e2b-it-abliteration-2-q8_0.gguf -c 2048

Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.

Step 1: Clone llama.cpp from GitHub.

git clone https://github.com/ggerganov/llama.cpp

Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL=1 flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).

cd llama.cpp && LLAMA_CURL=1 make

Step 3: Run inference through the main binary.

./llama-cli --hf-repo AlexHung29629/gemma-4-E2B-it-abliteration-2-Q8_0-GGUF --hf-file gemma-4-e2b-it-abliteration-2-q8_0.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo AlexHung29629/gemma-4-E2B-it-abliteration-2-Q8_0-GGUF --hf-file gemma-4-e2b-it-abliteration-2-q8_0.gguf -c 2048

README history 1 version

The author's README evolved over time. Click a version to see its content at that point.

  1. 2026-06-04Upload README.md with huggingface_hub926a4701.9 KB
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