Instructions to use huihui-ai/Huihui-Qwable-3.6-27b-abliterated-MTP-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use huihui-ai/Huihui-Qwable-3.6-27b-abliterated-MTP-GGUF with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("huihui-ai/Huihui-Qwable-3.6-27b-abliterated-MTP-GGUF", dtype="auto")

llama-cpp-python

How to use huihui-ai/Huihui-Qwable-3.6-27b-abliterated-MTP-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="huihui-ai/Huihui-Qwable-3.6-27b-abliterated-MTP-GGUF",
	filename="Huihui-Qwable-3.6-27b-abliterated-Q4_K_M_F16-MTP.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use huihui-ai/Huihui-Qwable-3.6-27b-abliterated-MTP-GGUF with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf huihui-ai/Huihui-Qwable-3.6-27b-abliterated-MTP-GGUF:Q4_K_M_F
# Run inference directly in the terminal:
llama cli -hf huihui-ai/Huihui-Qwable-3.6-27b-abliterated-MTP-GGUF:Q4_K_M_F

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf huihui-ai/Huihui-Qwable-3.6-27b-abliterated-MTP-GGUF:Q4_K_M_F
# Run inference directly in the terminal:
llama cli -hf huihui-ai/Huihui-Qwable-3.6-27b-abliterated-MTP-GGUF:Q4_K_M_F

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf huihui-ai/Huihui-Qwable-3.6-27b-abliterated-MTP-GGUF:Q4_K_M_F
# Run inference directly in the terminal:
./llama-cli -hf huihui-ai/Huihui-Qwable-3.6-27b-abliterated-MTP-GGUF:Q4_K_M_F

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf huihui-ai/Huihui-Qwable-3.6-27b-abliterated-MTP-GGUF:Q4_K_M_F
# Run inference directly in the terminal:
./build/bin/llama-cli -hf huihui-ai/Huihui-Qwable-3.6-27b-abliterated-MTP-GGUF:Q4_K_M_F

Use Docker

docker model run hf.co/huihui-ai/Huihui-Qwable-3.6-27b-abliterated-MTP-GGUF:Q4_K_M_F

LM Studio
Jan
Ollama
How to use huihui-ai/Huihui-Qwable-3.6-27b-abliterated-MTP-GGUF with Ollama:
```
ollama run hf.co/huihui-ai/Huihui-Qwable-3.6-27b-abliterated-MTP-GGUF:Q4_K_M_F
```

Unsloth Studio

How to use huihui-ai/Huihui-Qwable-3.6-27b-abliterated-MTP-GGUF with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for huihui-ai/Huihui-Qwable-3.6-27b-abliterated-MTP-GGUF to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for huihui-ai/Huihui-Qwable-3.6-27b-abliterated-MTP-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for huihui-ai/Huihui-Qwable-3.6-27b-abliterated-MTP-GGUF to start chatting

How to use huihui-ai/Huihui-Qwable-3.6-27b-abliterated-MTP-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf huihui-ai/Huihui-Qwable-3.6-27b-abliterated-MTP-GGUF:Q4_K_M_F

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "huihui-ai/Huihui-Qwable-3.6-27b-abliterated-MTP-GGUF:Q4_K_M_F"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use huihui-ai/Huihui-Qwable-3.6-27b-abliterated-MTP-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf huihui-ai/Huihui-Qwable-3.6-27b-abliterated-MTP-GGUF:Q4_K_M_F

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
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-Qwable-3.6-27b-abliterated-MTP-GGUF:Q4_K_M_F

Run Hermes

hermes

Atomic Chat new
Docker Model Runner
How to use huihui-ai/Huihui-Qwable-3.6-27b-abliterated-MTP-GGUF with Docker Model Runner:
```
docker model run hf.co/huihui-ai/Huihui-Qwable-3.6-27b-abliterated-MTP-GGUF:Q4_K_M_F
```

Lemonade

How to use huihui-ai/Huihui-Qwable-3.6-27b-abliterated-MTP-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull huihui-ai/Huihui-Qwable-3.6-27b-abliterated-MTP-GGUF:Q4_K_M_F

Run and chat with the model

lemonade run user.Huihui-Qwable-3.6-27b-abliterated-MTP-GGUF-Q4_K_M_F

List all available models

lemonade list

Huihui-Qwable-3.6-27b-abliterated-MTP-GGUF / README.md

huihui-ai

Update README.md

c40abf2 verified 4 days ago

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metadata

library_name: transformers
license: mit
base_model:
  - Mia-AiLab/Qwable-3.6-27b
tags:
  - multimodal
  - vision-language
  - audio
  - agent
  - video-understanding
  - long-context
  - abliterated
  - uncensored
  - GGUF
  - MTP

huihui-ai/Huihui-Qwable-3.6-27b-abliterated-MTP-GGUF

This is an uncensored version of Mia-AiLab/Qwable-3.6-27b created with abliteration.

This ablation was performed entirely using llama.cpp's GGUF model, without relying on Transformers,

For the specific ablation method, please refer to cvector-generator.

GGUF

Please use the latest version of ggml-org/llama.cpp

The version we tested is ggml-org/llama.cpp-b9190

apt-get update
apt-get install pciutils build-essential cmake curl libcurl4-openssl-dev -y
git clone https://github.com/ggml-org/llama.cpp
cmake llama.cpp -B llama.cpp/build \
    -DBUILD_SHARED_LIBS=OFF -DGGML_CUDA=ON
cmake --build llama.cpp/build --config Release -j --clean-first --target llama-cli llama-mtmd-cli llama-server llama-gguf-split
cp llama.cpp/build/bin/llama-* llama.cpp

./llama.cpp/llama-cli \
    -m huihui-ai/Huihui-Qwable-3.6-27b-abliterated-MTP-GGUF/Huihui-Qwen3.6-27B-abliterated-ggml-model-Q4_K.gguf \
    -ngl 99 -c 262144 -fa on -np 1 \
    --spec-type draft-mtp --spec-draft-n-max 6

Files

File	Size	out (`ffn_down/ssm_out/attn_output`)	Everything else
`Huihui-Qwable-3.6-27b-abliterated-Q4_K_M_Q8.gguf`	19.1 GiB	(`ffn_down/ssm_out/attn_output`) (Q8_0)	(`ffn_gate/ssm_out/ffn_up`) (Q4_K), (`attn_v/attn_qkv`) (Q6_K), MTP(blk.64.)
`Huihui-Qwable-3.6-27b-abliterated-Q4_K_M_F16.gguf`	25.8 GiB	(`ffn_down/ssm_out/attn_output`) (F16)	(`ffn_gate/ssm_out/ffn_up`) (Q4_K), (`attn_v/attn_qkv`) (Q6_K), MTP(blk.64.)
`Huihui-Qwable-3.6-27b-abliterated-F16.gguf`	50.9 GiB	(`ffn_down/ssm_out/attn_output`) (F16)	(`ffn_gate/ssm_out/ffn_up`) (F16) , (`attn_v/attn_qkv`) (F16), MTP(blk.64.)

Usage Warnings

Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs.
Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security.
Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences.
Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications.
Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content.
No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use.

Donation

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