Instructions to use HauhauCS/GLM-4.7-Flash-Uncensored-HauhauCS-Balanced with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use HauhauCS/GLM-4.7-Flash-Uncensored-HauhauCS-Balanced 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 HauhauCS/GLM-4.7-Flash-Uncensored-HauhauCS-Balanced:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf HauhauCS/GLM-4.7-Flash-Uncensored-HauhauCS-Balanced:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf HauhauCS/GLM-4.7-Flash-Uncensored-HauhauCS-Balanced:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf HauhauCS/GLM-4.7-Flash-Uncensored-HauhauCS-Balanced: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 HauhauCS/GLM-4.7-Flash-Uncensored-HauhauCS-Balanced:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf HauhauCS/GLM-4.7-Flash-Uncensored-HauhauCS-Balanced: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 HauhauCS/GLM-4.7-Flash-Uncensored-HauhauCS-Balanced:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf HauhauCS/GLM-4.7-Flash-Uncensored-HauhauCS-Balanced:Q4_K_M

Use Docker

docker model run hf.co/HauhauCS/GLM-4.7-Flash-Uncensored-HauhauCS-Balanced:Q4_K_M

LM Studio
Jan
Ollama
How to use HauhauCS/GLM-4.7-Flash-Uncensored-HauhauCS-Balanced with Ollama:
```
ollama run hf.co/HauhauCS/GLM-4.7-Flash-Uncensored-HauhauCS-Balanced:Q4_K_M
```

Unsloth Studio

How to use HauhauCS/GLM-4.7-Flash-Uncensored-HauhauCS-Balanced 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 HauhauCS/GLM-4.7-Flash-Uncensored-HauhauCS-Balanced 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 HauhauCS/GLM-4.7-Flash-Uncensored-HauhauCS-Balanced to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for HauhauCS/GLM-4.7-Flash-Uncensored-HauhauCS-Balanced to start chatting

How to use HauhauCS/GLM-4.7-Flash-Uncensored-HauhauCS-Balanced with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf HauhauCS/GLM-4.7-Flash-Uncensored-HauhauCS-Balanced: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": "HauhauCS/GLM-4.7-Flash-Uncensored-HauhauCS-Balanced:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

OpenClaw new

How to use HauhauCS/GLM-4.7-Flash-Uncensored-HauhauCS-Balanced with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf HauhauCS/GLM-4.7-Flash-Uncensored-HauhauCS-Balanced: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 "HauhauCS/GLM-4.7-Flash-Uncensored-HauhauCS-Balanced: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 HauhauCS/GLM-4.7-Flash-Uncensored-HauhauCS-Balanced with Docker Model Runner:
```
docker model run hf.co/HauhauCS/GLM-4.7-Flash-Uncensored-HauhauCS-Balanced:Q4_K_M
```

Lemonade

How to use HauhauCS/GLM-4.7-Flash-Uncensored-HauhauCS-Balanced with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull HauhauCS/GLM-4.7-Flash-Uncensored-HauhauCS-Balanced:Q4_K_M

Run and chat with the model

lemonade run user.GLM-4.7-Flash-Uncensored-HauhauCS-Balanced-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use HauhauCS/GLM-4.7-Flash-Uncensored-HauhauCS-Balanced with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf HauhauCS/GLM-4.7-Flash-Uncensored-HauhauCS-Balanced: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 HauhauCS/GLM-4.7-Flash-Uncensored-HauhauCS-Balanced:Q4_K_M

Run Hermes

hermes

Atomic Chat

GLM-4.7-Flash-Uncensored-HauhauCS-Balanced

Join the Discord for updates, roadmaps, projects, or just to chat.

GLM-4.7 Flash uncensored by HauhauCS.

About

No changes to datasets or capabilities. Fully functional, 100% of what the original authors intended - just without the refusals.

These are meant to be the best lossless uncensored models out there.

Agentic Coding

If you're doing agentic coding, use the Balanced variants. Good balance between capability and not refusing everything.

Downloads

File	Quant	Size
GLM-4.7-Flash-Uncensored-HauhauCS-Balanced-FP16.gguf	FP16	56 GB
GLM-4.7-Flash-Uncensored-HauhauCS-Balanced-Q8_0.gguf	Q8_0	30 GB
GLM-4.7-Flash-Uncensored-HauhauCS-Balanced-Q6_K.gguf	Q6_K	23 GB
GLM-4.7-Flash-Uncensored-HauhauCS-Balanced-Q4_K_M.gguf	Q4_K_M	17 GB

Specs

30B-A3B MoE (31B total, ~3B active per forward pass)
202K context
Based on zai-org/GLM-4.7-Flash

Recommended Settings

From the official Z.ai authors:

General use:

--temp 1.0 --top-p 0.95

Tool-calling / agentic:

--temp 0.7 --top-p 1.0

Important:

Disable repeat penalty (or --repeat-penalty 1.0)
For llama.cpp: use --min-p 0.01 (default 0.05 is too high)
Use --jinja flag for llama.cpp

Note: Not recommended for Ollama due to chat template issues. Works well with llama.cpp, LM Studio, Jan.

Usage

Works with llama.cpp, LM Studio, Jan, koboldcpp, etc.

Downloads last month: 4,018

GGUF

Model size

30B params

Architecture

deepseek2

Hardware compatibility

4-bit

6-bit

8-bit

View +1 variant

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GLM-4.7-Flash-Uncensored-HauhauCS-Balanced

GLM-4.7-Flash-Uncensored-HauhauCS-Balanced

About

Agentic Coding

Downloads

Specs

Recommended Settings

Usage

Spaces using HauhauCS/GLM-4.7-Flash-Uncensored-HauhauCS-Balanced 2