Huihui-GLM-5.2-abliterated-GGUF

Instructions to use Vladxximp/Huihui-GLM-5.2-abliterated-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Vladxximp/Huihui-GLM-5.2-abliterated-GGUF with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="Vladxximp/Huihui-GLM-5.2-abliterated-GGUF")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Vladxximp/Huihui-GLM-5.2-abliterated-GGUF", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use Vladxximp/Huihui-GLM-5.2-abliterated-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 Vladxximp/Huihui-GLM-5.2-abliterated-GGUF:UD-IQ1_M
# Run inference directly in the terminal:
llama cli -hf Vladxximp/Huihui-GLM-5.2-abliterated-GGUF:UD-IQ1_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Vladxximp/Huihui-GLM-5.2-abliterated-GGUF:UD-IQ1_M
# Run inference directly in the terminal:
llama cli -hf Vladxximp/Huihui-GLM-5.2-abliterated-GGUF:UD-IQ1_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 Vladxximp/Huihui-GLM-5.2-abliterated-GGUF:UD-IQ1_M
# Run inference directly in the terminal:
./llama-cli -hf Vladxximp/Huihui-GLM-5.2-abliterated-GGUF:UD-IQ1_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 Vladxximp/Huihui-GLM-5.2-abliterated-GGUF:UD-IQ1_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Vladxximp/Huihui-GLM-5.2-abliterated-GGUF:UD-IQ1_M

Use Docker

docker model run hf.co/Vladxximp/Huihui-GLM-5.2-abliterated-GGUF:UD-IQ1_M

LM Studio
Jan

vLLM

How to use Vladxximp/Huihui-GLM-5.2-abliterated-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Vladxximp/Huihui-GLM-5.2-abliterated-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": "Vladxximp/Huihui-GLM-5.2-abliterated-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Vladxximp/Huihui-GLM-5.2-abliterated-GGUF:UD-IQ1_M

SGLang

How to use Vladxximp/Huihui-GLM-5.2-abliterated-GGUF with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "Vladxximp/Huihui-GLM-5.2-abliterated-GGUF" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Vladxximp/Huihui-GLM-5.2-abliterated-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "Vladxximp/Huihui-GLM-5.2-abliterated-GGUF" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Vladxximp/Huihui-GLM-5.2-abliterated-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Ollama
How to use Vladxximp/Huihui-GLM-5.2-abliterated-GGUF with Ollama:
```
ollama run hf.co/Vladxximp/Huihui-GLM-5.2-abliterated-GGUF:UD-IQ1_M
```
Unsloth Desktop

How to use Vladxximp/Huihui-GLM-5.2-abliterated-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Vladxximp/Huihui-GLM-5.2-abliterated-GGUF:UD-IQ1_M

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "Vladxximp/Huihui-GLM-5.2-abliterated-GGUF:UD-IQ1_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use Vladxximp/Huihui-GLM-5.2-abliterated-GGUF with Docker Model Runner:
```
docker model run hf.co/Vladxximp/Huihui-GLM-5.2-abliterated-GGUF:UD-IQ1_M
```

Lemonade

How to use Vladxximp/Huihui-GLM-5.2-abliterated-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Vladxximp/Huihui-GLM-5.2-abliterated-GGUF:UD-IQ1_M

Run and chat with the model

lemonade run user.Huihui-GLM-5.2-abliterated-GGUF-UD-IQ1_M

List all available models

lemonade list

Hermes Agent

How to use Vladxximp/Huihui-GLM-5.2-abliterated-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 Vladxximp/Huihui-GLM-5.2-abliterated-GGUF:UD-IQ1_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 Vladxximp/Huihui-GLM-5.2-abliterated-GGUF:UD-IQ1_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use Vladxximp/Huihui-GLM-5.2-abliterated-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Vladxximp/Huihui-GLM-5.2-abliterated-GGUF:UD-IQ1_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 "Vladxximp/Huihui-GLM-5.2-abliterated-GGUF:UD-IQ1_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"

Vladxximp

huihui-ai commited on Jul 5

Commit

1a3acbb

0 Parent(s):

Duplicate from huihui-ai/Huihui-GLM-5.2-abliterated-GGUF

Browse files

Co-authored-by: huihui.ai <[email protected]>

Files changed (24) hide show

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+---
+language:
+- en
+- zh
+library_name: transformers
+license: mit
+pipeline_tag: text-generation
+base_model:
+- zai-org/GLM-5.2
+tags:
+- glm_moe_dsa
+- unsloth
+- abliterated
+- uncensored
+- GGUF
+- huihui
+extra_gated_prompt: >-
+    **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.
+---
+# huihui-ai/Huihui-GLM-5.2-abliterated-GGUF
+This is an uncensored version of [zai-org/GLM-5.2](https://huggingface.co/zai-org/GLM-5.2) created with abliteration (see [remove-refusals-with-transformers](https://github.com/Sumandora/remove-refusals-with-transformers) to know more about it).
+This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens.
+**Note** We will directly perform ablation on the GGUF files from [unsloth/GLM-5.2-GGUF](https://huggingface.co/unsloth/GLM-5.2-GGUF). Some weights quantized in Q5_K and Q6_K will be converted to Q8_0. This time, the weights of the first 12 layers and all expert modules were not ablated, so the final weights will increase, but the change will not be significant. The UD-IQ1_M is only 3GB larger than the original.
+Some weights quantized in Q5_K and Q6_K, Q8_0 will be converted to MXFP4 (UD-Q2_K_XL -> UD-Q2_K_MXFP4)
+## Download and merge
+Use the [llama.cpp](https://github.com/ggml-org/llama.cpp) split program to merge model (llama-gguf-split needs to be compiled.),
+```
+huggingface-cli download huihui-ai/Huihui-GLM-5.2-abliterated-GGUF --local-dir ./huihui-ai/Huihui-GLM-5.2-abliterated-GGUF --token xxx
+llama-gguf-split --merge huihui-ai/Huihui-GLM-5.2-abliterated-GGUF/UD-IQ1_M/GLM-5.2-UD-IQ1_M-00001-of-00006.gguf huihui-ai/Huihui-GLM-5.2-abliterated-GGUF/GLM-5.2-UD-IQ1_M.gguf
+```
+### 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
+If you like it, please click 'like' and follow us for more updates.
+You can follow [x.com/support_huihui](https://x.com/support_huihui) to get the latest model information from huihui.ai.
+##### Your donation helps us continue our further development and improvement, a cup of coffee can do it.
+- bitcoin（BTC):
+```
+  bc1qqnkhuchxw0zqjh2ku3lu4hq45hc6gy84uk70ge
+```
+- Support our work on Ko-fi (https://ko-fi.com/huihuiai)!

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