@support_huihui: 新增GGUF模型：huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF 这是empero-ai/Qw…的未经审查版本

X AI KOLs Timeline 模型
gguf uncensored abliteration quantized open-source model-release

摘要

一款新的未经审查的GGUF量化版Qwythos-9B-Claude-Mythos-5-1M模型，通过abliteration技术创建，现已发布在Hugging Face上。

新增GGUF模型： huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF 这是通过abliteration技术创建的empero-ai/Qwythos-9B-Claude-Mythos-5-1M的未经审查版本。 注意：在非思考模式下，该模型严格遵循第一个提示词的指令，仅输出所请求的内容——无论是翻译还是特定格式——没有任何开场白或结束语。
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缓存时间: 2026/06/26 06:06

新的 GGUF：huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF
这是通过 abliteration 技术从 empero-ai/Qwythos-9B-Claude-Mythos-5-1M 创建的无审查版本。
注意：在非思考模式下，该模型严格遵守第一条指令，只提供所请求的输出——无论是翻译还是特定格式——没有任何开场白或结束语。

huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF · Hugging Face

来源：https://huggingface.co/huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF
库
Transformers (https://huggingface.co/huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF?library=transformers)
如何使用 huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF 与 Transformers：

# 使用管道作为高级助手
from transformers import pipeline

pipe = pipeline("text-generation", model="huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF")
messages = [
    {"role": "user", "content": "你是谁？"},
]
pipe(messages)

# 直接加载模型
from transformers import AutoModel

model = AutoModel.from_pretrained("huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF", dtype="auto")

llama-cpp-python (https://huggingface.co/huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF?library=llama-cpp-python)
如何使用 huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF 与 llama-cpp-python：

# !pip install llama-cpp-python
from llama_cpp import Llama

llm = Llama.from_pretrained(
    repo_id="huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF",
    filename="Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-Q4_K.gguf",
)

llm.create_chat_completion(
    messages=[
        {
            "role": "user",
            "content": "法国的首都是哪里？"
        }
    ]
)

笔记本
Google Colab (https://huggingface.co/huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF/colab)
Kaggle (https://huggingface.co/huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF/kaggle)
本地应用
设置 (https://huggingface.co/settings/local-apps)
llama.cpp (https://huggingface.co/huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF?local-app=llama.cpp)
如何使用 huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF 与 llama.cpp：

安装 (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh

# 启动一个本地 OpenAI 兼容的服务，附带 Web 界面：
llama serve -hf huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF:Q6_K

# 直接在终端运行推理：
llama cli -hf huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF:Q6_K
从 WinGet 安装 (Windows)
winget install llama.cpp

# 启动一个本地 OpenAI 兼容的服务，附带 Web 界面：
llama serve -hf huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF:Q6_K

# 直接在终端运行推理：
llama cli -hf huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF:Q6_K
使用预编译二进制文件
# 从以下地址下载预编译二进制文件：
# https://github.com/ggerganov/llama.cpp/releases

# 启动一个本地 OpenAI 兼容的服务，附带 Web 界面：
./llama-server -hf huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF:Q6_K

# 直接在终端运行推理：
./llama-cli -hf huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF:Q6_K
从源码构建
git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli

# 启动一个本地 OpenAI 兼容的服务，附带 Web 界面：
./build/bin/llama-server -hf huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF:Q6_K

# 直接在终端运行推理：
./build/bin/llama-cli -hf huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF:Q6_K
使用 Docker
docker model run hf.co/huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF:Q6_K

LM Studio
Jan
vLLM (https://huggingface.co/huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF?local-app=vllm)
如何使用 huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF 与 vLLM：

从 pip 安装并服务模型
# 从 pip 安装 vLLM：
pip install vllm

# 启动 vLLM 服务：
vllm serve "huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF"

# 使用 curl 调用服务（OpenAI 兼容 API）：
curl -X POST "http://localhost:8000/v1/chat/completions" \
-H "Content-Type: application/json" \
--data '{
  "model": "huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF",
  "messages": [
    {
      "role": "user",
      "content": "法国的首都是哪里？"
    }
  ]
}'
使用 Docker
docker model run hf.co/huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF:Q6_K

SGLang (https://huggingface.co/huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF?local-app=sglang)
如何使用 huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF 与 SGLang：

从 pip 安装并服务模型
# 从 pip 安装 SGLang：
pip install sglang

# 启动 SGLang 服务：
python3 -m sglang.launch_server \
    --model-path "huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF" \
    --host 0.0.0.0 \
    --port 30000

# 使用 curl 调用服务（OpenAI 兼容 API）：
curl -X POST "http://localhost:30000/v1/chat/completions" \
-H "Content-Type: application/json" \
--data '{
  "model": "huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF",
  "messages": [
    {
      "role": "user",
      "content": "法国的首都是哪里？"
    }
  ]
}'
使用 Docker 镜像
docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
    --model-path "huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF" \
    --host 0.0.0.0 \
    --port 30000

# 使用 curl 调用服务（OpenAI 兼容 API）：
curl -X POST "http://localhost:30000/v1/chat/completions" \
-H "Content-Type: application/json" \
--data '{
  "model": "huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF",
  "messages": [
    {
      "role": "user",
      "content": "法国的首都是哪里？"
    }
  ]
}'

Ollama (https://huggingface.co/huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF?local-app=ollama)
如何使用 huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF 与 Ollama：

ollama run hf.co/huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF:Q6_K

Unsloth Studio (https://huggingface.co/huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF?local-app=unsloth)
如何使用 huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF 与 Unsloth Studio：

安装 Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh

# 运行 unsloth studio
unsloth studio -H 0.0.0.0 -p 8888

# 然后在浏览器中打开 http://localhost:8888
# 搜索 huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF 开始聊天
安装 Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex

# 运行 unsloth studio
unsloth studio -H 0.0.0.0 -p 8888

# 然后在浏览器中打开 http://localhost:8888
# 搜索 huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF 开始聊天
使用 HuggingFace Spaces 运行 Unsloth
# 无需设置
# 在浏览器中打开 https://huggingface.co/spaces/unsloth/studio
# 搜索 huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF 开始聊天

Pi (https://huggingface.co/huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF?local-app=pi)
如何使用 huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF 与 Pi：

启动 llama.cpp 服务
# 安装 llama.cpp：
brew install llama.cpp

# 启动一个本地 OpenAI 兼容的服务：
llama serve -hf huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF:Q6_K
在 Pi 中配置模型
# 安装 Pi：
npm install -g @mariozechner/pi-coding-agent

# 添加到 ~/.pi/agent/models.json：
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF:Q6_K"
        }
      ]
    }
  }
}
运行 Pi
# 在项目目录中启动 Pi：
pi

Hermes Agentnew (https://huggingface.co/huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF?local-app=hermes-agent)
如何使用 huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF 与 Hermes Agent：

启动 llama.cpp 服务
# 安装 llama.cpp：
brew install llama.cpp

# 启动一个本地 OpenAI 兼容的服务：
llama serve -hf huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF:Q6_K
配置 Hermes
# 安装 Hermes：
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup

# 将 Hermes 指向本地服务：
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF:Q6_K
运行 Hermes
hermes

Atomic Chatnew
Docker Model Runner (https://huggingface.co/huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF?local-app=docker-model-runner)
如何使用 huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF 与 Docker Model Runner：

docker model run hf.co/huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF:Q6_K

Lemonade (https://huggingface.co/huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF?local-app=lemonade)
如何使用 huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF 与 Lemonade：

拉取模型
# 从 https://lemonade-server.ai/ 下载 Lemonade
lemonade pull huihui-ai/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF:Q6_K
运行并与模型聊天
lemonade run user.Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-GGUF-Q6_K
列出所有可用模型
lemonade list

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