Instructions to use hell0ks/Solar-Open-100B-jailbreak-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hell0ks/Solar-Open-100B-jailbreak-gguf with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="hell0ks/Solar-Open-100B-jailbreak-gguf") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("hell0ks/Solar-Open-100B-jailbreak-gguf", dtype="auto") - llama-cpp-python
How to use hell0ks/Solar-Open-100B-jailbreak-gguf with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="hell0ks/Solar-Open-100B-jailbreak-gguf", filename="model-Q4_K_M-00001-of-00007.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use hell0ks/Solar-Open-100B-jailbreak-gguf with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf hell0ks/Solar-Open-100B-jailbreak-gguf:Q4_K_M # Run inference directly in the terminal: llama-cli -hf hell0ks/Solar-Open-100B-jailbreak-gguf:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf hell0ks/Solar-Open-100B-jailbreak-gguf:Q4_K_M # Run inference directly in the terminal: llama-cli -hf hell0ks/Solar-Open-100B-jailbreak-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 hell0ks/Solar-Open-100B-jailbreak-gguf:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf hell0ks/Solar-Open-100B-jailbreak-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 hell0ks/Solar-Open-100B-jailbreak-gguf:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf hell0ks/Solar-Open-100B-jailbreak-gguf:Q4_K_M
Use Docker
docker model run hf.co/hell0ks/Solar-Open-100B-jailbreak-gguf:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use hell0ks/Solar-Open-100B-jailbreak-gguf with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "hell0ks/Solar-Open-100B-jailbreak-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": "hell0ks/Solar-Open-100B-jailbreak-gguf", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/hell0ks/Solar-Open-100B-jailbreak-gguf:Q4_K_M
- SGLang
How to use hell0ks/Solar-Open-100B-jailbreak-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 "hell0ks/Solar-Open-100B-jailbreak-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": "hell0ks/Solar-Open-100B-jailbreak-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 "hell0ks/Solar-Open-100B-jailbreak-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": "hell0ks/Solar-Open-100B-jailbreak-gguf", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Ollama
How to use hell0ks/Solar-Open-100B-jailbreak-gguf with Ollama:
ollama run hf.co/hell0ks/Solar-Open-100B-jailbreak-gguf:Q4_K_M
- Unsloth Studio
How to use hell0ks/Solar-Open-100B-jailbreak-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 hell0ks/Solar-Open-100B-jailbreak-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 hell0ks/Solar-Open-100B-jailbreak-gguf to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for hell0ks/Solar-Open-100B-jailbreak-gguf to start chatting
- Pi
How to use hell0ks/Solar-Open-100B-jailbreak-gguf with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf hell0ks/Solar-Open-100B-jailbreak-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": "hell0ks/Solar-Open-100B-jailbreak-gguf:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use hell0ks/Solar-Open-100B-jailbreak-gguf with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf hell0ks/Solar-Open-100B-jailbreak-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 hell0ks/Solar-Open-100B-jailbreak-gguf:Q4_K_M
Run Hermes
hermes
- Docker Model Runner
How to use hell0ks/Solar-Open-100B-jailbreak-gguf with Docker Model Runner:
docker model run hf.co/hell0ks/Solar-Open-100B-jailbreak-gguf:Q4_K_M
- Lemonade
How to use hell0ks/Solar-Open-100B-jailbreak-gguf with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull hell0ks/Solar-Open-100B-jailbreak-gguf:Q4_K_M
Run and chat with the model
lemonade run user.Solar-Open-100B-jailbreak-gguf-Q4_K_M
List all available models
lemonade list
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf hell0ks/Solar-Open-100B-jailbreak-gguf:# Run inference directly in the terminal:
llama-cli -hf hell0ks/Solar-Open-100B-jailbreak-gguf: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 hell0ks/Solar-Open-100B-jailbreak-gguf:# Run inference directly in the terminal:
./llama-cli -hf hell0ks/Solar-Open-100B-jailbreak-gguf: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 hell0ks/Solar-Open-100B-jailbreak-gguf:# Run inference directly in the terminal:
./build/bin/llama-cli -hf hell0ks/Solar-Open-100B-jailbreak-gguf:Use Docker
docker model run hf.co/hell0ks/Solar-Open-100B-jailbreak-gguf:Overview
This is a GGUF quantized, and modified version of Solar-Open-100B, using Multi-Directional Refusal Suppression methodology.
For full model, see hell0ks/Solar-Open-100B-jailbreak
Why?
- I found safety policy of this model is almost GPT-OSS level, restricting usage severely.
- To experiment SOM-based method is viable on tricky cases.
How I did it
- Extract Self-Organizing Maps (SOMs) from 3 testing sets on different layers
- Hard prompts: "I'm sorry, I can't help."
- Soft prompts: "I'm sorry, I can't help. But.."
- Policy refusals (Reasoning): "It is ~. It's against ~ policy."
- Apply conventional abliterate method using vectors
Result
- Hard prompts: It will try checking against policy, but eventually confused about policy itself.
- Soft prompts: It will do response without policy checking.
Side Effect
- May hallucinate more
- May have some impact on model's intelligence
Notice
- I can't guarantee that model will not refuse on every prompt.
- You should NOT use it in any production environment.
- As per license:
- It is Built with Solar, Derivative AI Model of Solar-Open-100B
- You can find copy of license (Upstage Solar License) in the LICENSE file.
Acknowledgement
- Downloads last month
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Model tree for hell0ks/Solar-Open-100B-jailbreak-gguf
Base model
upstage/Solar-Open-100B
Install from brew
# Start a local OpenAI-compatible server with a web UI: llama-server -hf hell0ks/Solar-Open-100B-jailbreak-gguf:# Run inference directly in the terminal: llama-cli -hf hell0ks/Solar-Open-100B-jailbreak-gguf: