ModelHub XC 61334dea6c 初始化项目,由ModelHub XC社区提供模型
Model: Gideon531/Huihui-Qwen3-8B-abliterated-v2-Q8_0-GGUF
Source: Original Platform
2026-04-10 22:38:58 +08:00

library_name, license, license_link, pipeline_tag, base_model, tags
library_name license license_link pipeline_tag base_model tags
transformers apache-2.0 https://huggingface.co/Qwen/Qwen3-8B/blob/main/LICENSE text-generation huihui-ai/Huihui-Qwen3-8B-abliterated-v2
chat
abliterated
uncensored
llama-cpp
gguf-my-repo

Gideon531/Huihui-Qwen3-8B-abliterated-v2-Q8_0-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 Gideon531/Huihui-Qwen3-8B-abliterated-v2-Q8_0-GGUF --hf-file huihui-qwen3-8b-abliterated-v2-q8_0.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo Gideon531/Huihui-Qwen3-8B-abliterated-v2-Q8_0-GGUF --hf-file huihui-qwen3-8b-abliterated-v2-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 Gideon531/Huihui-Qwen3-8B-abliterated-v2-Q8_0-GGUF --hf-file huihui-qwen3-8b-abliterated-v2-q8_0.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo Gideon531/Huihui-Qwen3-8B-abliterated-v2-Q8_0-GGUF --hf-file huihui-qwen3-8b-abliterated-v2-q8_0.gguf -c 2048
Description
Model synced from source: Gideon531/Huihui-Qwen3-8B-abliterated-v2-Q8_0-GGUF
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