zen-designer-gguf

Instructions to use zenlm/zen-designer-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use zenlm/zen-designer-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 zenlm/zen-designer-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf zenlm/zen-designer-gguf:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf zenlm/zen-designer-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf zenlm/zen-designer-gguf:Q4_K_M

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 zenlm/zen-designer-gguf:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf zenlm/zen-designer-gguf:Q4_K_M

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 zenlm/zen-designer-gguf:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf zenlm/zen-designer-gguf:Q4_K_M

Use Docker

docker model run hf.co/zenlm/zen-designer-gguf:Q4_K_M

LM Studio
Jan

vLLM

How to use zenlm/zen-designer-gguf with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "zenlm/zen-designer-gguf"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "zenlm/zen-designer-gguf",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/zenlm/zen-designer-gguf:Q4_K_M

Ollama
How to use zenlm/zen-designer-gguf with Ollama:
```
ollama run hf.co/zenlm/zen-designer-gguf:Q4_K_M
```

Unsloth Studio

How to use zenlm/zen-designer-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 zenlm/zen-designer-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 zenlm/zen-designer-gguf to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for zenlm/zen-designer-gguf to start chatting

How to use zenlm/zen-designer-gguf with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf zenlm/zen-designer-gguf:Q4_K_M

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": "zenlm/zen-designer-gguf:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use zenlm/zen-designer-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 zenlm/zen-designer-gguf:Q4_K_M

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 zenlm/zen-designer-gguf:Q4_K_M

Run Hermes

hermes

OpenClaw new

How to use zenlm/zen-designer-gguf with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf zenlm/zen-designer-gguf:Q4_K_M

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "zenlm/zen-designer-gguf:Q4_K_M" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

Docker Model Runner
How to use zenlm/zen-designer-gguf with Docker Model Runner:
```
docker model run hf.co/zenlm/zen-designer-gguf:Q4_K_M
```

Lemonade

How to use zenlm/zen-designer-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull zenlm/zen-designer-gguf:Q4_K_M

Run and chat with the model

lemonade run user.zen-designer-gguf-Q4_K_M

List all available models

lemonade list

Atomic Chat

zeekay commited on Feb 27

Commit

5e58ccb

verified ·

1 Parent(s): 806c2d7

docs: add Zen Designer GGUF README with abliteration documentation

Browse files

Files changed (1) hide show

README.md +91 -34

README.md CHANGED Viewed

@@ -1,65 +1,122 @@
 ---
 license: apache-2.0
-pipeline_tag: image-text-to-text
-library_name: transformers
-base_model:
-- Qwen/Qwen3-VL-235B-A22B-Instruct
 tags:
 - abliterated
-- uncensored
-- GGUF
 ---
-# huihui-ai/Huihui-Qwen3-VL-235B-A22B-Instruct-abliterated-GGUF
-This is an uncensored version of [Qwen/Qwen3-VL-235B-A22B-Instruct](https://huggingface.co/Qwen/Qwen3-VL-235B-A22B-Instruct) created with abliteration (see [remove-refusals-with-transformers](https://github.com/Sumandora/remove-refusals-with-transformers) to know more about it).
-It was only the text part that was processed, not the image part.
-The abliterated model will no longer say "I can’t describe or analyze this image."
-## GGUF
-The official [llama.cpp-b6907](https://github.com/ggml-org/llama.cpp/releases/tag/b6907) has now been updated to support Qwen3-VL conversion to GGUF format and can be tested using  llama-mtmd-cli.
-```
-huggingface-cli download huihui-ai/Huihui-Qwen3-VL-235B-A22B-Instruct-abliterated-GGUF --local-dir ./huihui-ai/Huihui-Qwen3-VL-235B-A22B-Instruct-abliterated-GGUF --token xxx
-llama-gguf-split --merge huihui-ai/Huihui-Qwen3-VL-235B-A22B-Instruct-abliterated-GGUF/GGUF/Q2_K/Q2_K-00001-of-00002.gguf huihui-ai/Huihui-Qwen3-VL-235B-A22B-Instruct-abliterated-GGUF/GGUF/Q2_K.gguf
-llama-mtmd-cli -m huihui-ai/Huihui-Qwen3-VL-235B-A22B-Instruct-abliterated-GGUF/GGUF/Q2_K.gguf --mmproj huihui-ai/Huihui-Qwen3-VL-235B-A22B-Instruct-abliterated-GGUF/GGUF/mmproj-ggml-model-f16.gguf -c 4096 --image png/cc.jpg -p "Describe this image."
 ```
-If it's just for chatting, you can use llama-cli.
-```
-llama-cli -m huihui-ai/Huihui-Qwen3-VL-235B-A22B-Instruct-abliterated-GGUF/GGUF/Q2_K.gguf -c 40960
-```
-### 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)!

 ---
+language:
+- en
+- zh
+- ja
+- ko
+- fr
+- de
+- es
+- pt
+- it
+- ru
 license: apache-2.0
 tags:
+- text-generation
+- vision
+- multimodal
+- zenlm
+- zen
+- gguf
 - abliterated
+- moe
+- ocr
+- document-understanding
+pipeline_tag: text-generation
 ---
+# Zen Designer GGUF: 235B Vision-Language Model (Abliterated)
+**235B MoE | Vision-Language | GGUF Quantized | Abliterated**
+GGUF quantized and abliterated version of [Zen Designer](https://huggingface.co/zenlm/zen-designer-235b-a22b-instruct) — the 235B flagship vision-language model from Zen LM. Supports images, video, documents, charts, GUIs, and spatial reasoning with 256K context.
+---
+## Model Specifications
+| Attribute | Value |
+|-----------|-------|
+| Parameters | 235B total / 22B active (MoE) |
+| Architecture | Vision-language transformer (Mixture of Experts) |
+| Context Window | 256K tokens |
+| Modalities | Text, Images, Video, Documents |
+| OCR Languages | 32 scripts |
+| License | Apache 2.0 |
+---
+## Available Formats
+| Format | Size | Description | Recommended Use |
+|--------|------|-------------|-----------------|
+| Q2_K (split) | ~60 GB | 2-bit quantization, 15-part split | Servers with 64+ GB RAM, maximum scale |
+| Q4_K_M | ~142 GB | 4-bit quantization, single or split | Best quality/size tradeoff for local inference |
+---
+## Quick Start
+### llama.cpp
+```bash
+# Download a split (Q2_K example — replace with Q4_K_M filename as appropriate)
+# Then run:
+llama-cli \
+  --model zen-designer-235b-a22b-instruct-abliterated-Q2_K-00001-of-00015.gguf \
+  --mmproj mmproj-zen-designer-235b-a22b-instruct-abliterated-f16.gguf \
+  --image your_image.jpg \
+  --prompt "Describe this image in detail." \
+  -n 1024 \
+  --ctx-size 8192 \
+  --temp 0.7
 ```
+For multi-part files, place all split parts in the same directory and point `--model` to part `00001`.
+### Vision Tasks
+Zen Designer handles a broad range of visual inputs:
+- Image analysis and description
+- Document and PDF parsing
+- Chart and table extraction
+- GUI navigation and screen understanding
+- Video understanding with temporal reasoning
+- Bounding box and spatial grounding
+---
+## Abliteration
+This model has been abliterated — a technique that removes refusal behaviors encoded in the model weights without fine-tuning. The process works by identifying the refusal direction in the model's residual stream and projecting it out of the weight matrices.
+**What abliteration does:**
+- Removes hardcoded refusal responses
+- Preserves all other capabilities and knowledge
+- Does not alter factual knowledge or reasoning ability
+**What abliteration does not do:**
+- Add harmful knowledge the base model lacked
+- Guarantee any specific behavior
+- Replace a system prompt or application-level safety policy
+Users are responsible for appropriate deployment and use of abliterated models. Apply system prompts and application-layer controls to define model behavior for your use case.
+---
+## Model Family
+| Model | Format | Parameters | Context |
+|-------|--------|-----------|---------|
+| [zen-designer-235b-a22b-instruct](https://huggingface.co/zenlm/zen-designer-235b-a22b-instruct) | SafeTensors | 235B / 22B active | 256K |
+| [zen-designer-gguf](https://huggingface.co/zenlm/zen-designer-gguf) | GGUF | 235B / 22B active | 256K |
+---
+## Links
+[Zen LM](https://zenlm.org) | [Hanzo AI](https://hanzo.ai) | [GitHub](https://github.com/zenlm) | [All Models](https://huggingface.co/zenlm)
+---
+Part of the Zen model family ([zenlm.org](https://zenlm.org)) by [Hanzo AI](https://hanzo.ai) (Techstars '17) and [Zoo Labs Foundation](https://zoo.ngo) (zoo.ngo).