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Medvedko/Huihui-Qwen3-8B-abliterated-v2-Q5_K_M-GGUF overview

Medvedko/Huihui Qwen3 8B abliterated v2 Q5 K M GGUF This model was converted to GGUF format from huihui ai/Huihui Qwen3 8B abliterated v2 https://huggingface.c…

transformersggufchatabliterateduncensoredllama-cppgguf-my-repotext-generationbase_model:huihui-ai/Huihui-Qwen3-8B-abliterated-v2base_model:quantized:huihui-ai/Huihui-Qwen3-8B-abliterated-v2license:apache-2.0endpoints_compatibleregion:us

Runs locally from ~5.45 GB disk (8 GB VRAM class GPUs with llama.cpp / guIDE).

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Pipeline
text-generation
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Repository Files & Downloads

1 GGUF files detected
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huihui-qwen3-8b-abliterated-v2-q5_k_m.ggufGGUFQ5_K_M5.45 GBDownload

Model Details

Model IDMedvedko/Huihui-Qwen3-8B-abliterated-v2-Q5_K_M-GGUF
AuthorMedvedko
Pipelinetext-generation
Licenseapache-2.0
Base modelhuihui-ai/Huihui-Qwen3-8B-abliterated-v2
Last modified2026-07-12T11:21:40.000Z

Model README

---

library_name: transformers

license: apache-2.0

license_link: https://huggingface.co/Qwen/Qwen3-8B/blob/main/LICENSE

pipeline_tag: text-generation

base_model: huihui-ai/Huihui-Qwen3-8B-abliterated-v2

tags:

  • chat
  • abliterated
  • uncensored
  • llama-cpp
  • gguf-my-repo

---

Medvedko/Huihui-Qwen3-8B-abliterated-v2-Q5_K_M-GGUF

This model was converted to GGUF format from huihui-ai/Huihui-Qwen3-8B-abliterated-v2 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 Medvedko/Huihui-Qwen3-8B-abliterated-v2-Q5_K_M-GGUF --hf-file huihui-qwen3-8b-abliterated-v2-q5_k_m.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo Medvedko/Huihui-Qwen3-8B-abliterated-v2-Q5_K_M-GGUF --hf-file huihui-qwen3-8b-abliterated-v2-q5_k_m.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 Medvedko/Huihui-Qwen3-8B-abliterated-v2-Q5_K_M-GGUF --hf-file huihui-qwen3-8b-abliterated-v2-q5_k_m.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo Medvedko/Huihui-Qwen3-8B-abliterated-v2-Q5_K_M-GGUF --hf-file huihui-qwen3-8b-abliterated-v2-q5_k_m.gguf -c 2048

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