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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	---
	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](https://huggingface.co/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](https://github.com/ggml-org/llama.cpp/blob/master/tools/cvector-generator/README.md).


	## GGUF

	Please use the latest version of [ggml-org/llama.cpp](https://github.com/ggml-org/llama.cpp/releases)

	The version we tested is [ggml-org/llama.cpp-b9190](https://github.com/ggml-org/llama.cpp/releases/tag/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
	##### Your donation helps us continue our further development and improvement, a cup of coffee can do it.
	- bitcoin:
	```
	bc1qqnkhuchxw0zqjh2ku3lu4hq45hc6gy84uk70ge
	```
	- Support our work on [Ko-fi](https://ko-fi.com/huihuiai)!