Instructions to use jackasda211233/Qwen3.5-27B-Uncensored-RYS-Reasoner-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use jackasda211233/Qwen3.5-27B-Uncensored-RYS-Reasoner-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 jackasda211233/Qwen3.5-27B-Uncensored-RYS-Reasoner-GGUF:BF16 # Run inference directly in the terminal: llama cli -hf jackasda211233/Qwen3.5-27B-Uncensored-RYS-Reasoner-GGUF:BF16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf jackasda211233/Qwen3.5-27B-Uncensored-RYS-Reasoner-GGUF:BF16 # Run inference directly in the terminal: llama cli -hf jackasda211233/Qwen3.5-27B-Uncensored-RYS-Reasoner-GGUF:BF16
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 jackasda211233/Qwen3.5-27B-Uncensored-RYS-Reasoner-GGUF:BF16 # Run inference directly in the terminal: ./llama-cli -hf jackasda211233/Qwen3.5-27B-Uncensored-RYS-Reasoner-GGUF:BF16
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 jackasda211233/Qwen3.5-27B-Uncensored-RYS-Reasoner-GGUF:BF16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf jackasda211233/Qwen3.5-27B-Uncensored-RYS-Reasoner-GGUF:BF16
Use Docker
docker model run hf.co/jackasda211233/Qwen3.5-27B-Uncensored-RYS-Reasoner-GGUF:BF16
- LM Studio
- Jan
- vLLM
How to use jackasda211233/Qwen3.5-27B-Uncensored-RYS-Reasoner-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "jackasda211233/Qwen3.5-27B-Uncensored-RYS-Reasoner-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": "jackasda211233/Qwen3.5-27B-Uncensored-RYS-Reasoner-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/jackasda211233/Qwen3.5-27B-Uncensored-RYS-Reasoner-GGUF:BF16
- Ollama
How to use jackasda211233/Qwen3.5-27B-Uncensored-RYS-Reasoner-GGUF with Ollama:
ollama run hf.co/jackasda211233/Qwen3.5-27B-Uncensored-RYS-Reasoner-GGUF:BF16
- Unsloth Desktop
- Pi
How to use jackasda211233/Qwen3.5-27B-Uncensored-RYS-Reasoner-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf jackasda211233/Qwen3.5-27B-Uncensored-RYS-Reasoner-GGUF:BF16
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": "jackasda211233/Qwen3.5-27B-Uncensored-RYS-Reasoner-GGUF:BF16" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use jackasda211233/Qwen3.5-27B-Uncensored-RYS-Reasoner-GGUF with Docker Model Runner:
docker model run hf.co/jackasda211233/Qwen3.5-27B-Uncensored-RYS-Reasoner-GGUF:BF16
- Lemonade
How to use jackasda211233/Qwen3.5-27B-Uncensored-RYS-Reasoner-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull jackasda211233/Qwen3.5-27B-Uncensored-RYS-Reasoner-GGUF:BF16
Run and chat with the model
lemonade run user.Qwen3.5-27B-Uncensored-RYS-Reasoner-GGUF-BF16
List all available models
lemonade list
- Hermes Agent
How to use jackasda211233/Qwen3.5-27B-Uncensored-RYS-Reasoner-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 jackasda211233/Qwen3.5-27B-Uncensored-RYS-Reasoner-GGUF:BF16
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 jackasda211233/Qwen3.5-27B-Uncensored-RYS-Reasoner-GGUF:BF16
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use jackasda211233/Qwen3.5-27B-Uncensored-RYS-Reasoner-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf jackasda211233/Qwen3.5-27B-Uncensored-RYS-Reasoner-GGUF:BF16
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 "jackasda211233/Qwen3.5-27B-Uncensored-RYS-Reasoner-GGUF:BF16" \ --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"
Upload README.md with huggingface_hub
Browse files
README.md
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@@ -36,6 +36,26 @@ An uncensored, coding-focused Qwen3.5-27B with RYS (Repeat Your Self) layer dupl
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## Why This Model Exists
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The standard Qwen3.5-27B is an exceptional model, but its safety guardrails actively interfere with legitimate development workflows:
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- **SSH/Network access refusal**: The base model refuses to SSH into the user's own machines, citing "security risks" β making it unusable as a remote development agent
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## Why This Model Exists
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### The Censorship Problem
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Over the past several years, the author has observed a consistent trend of **increasing censorship across all major model releases** β particularly in domains where unrestricted knowledge is most critical: biology, legal studies, and medicine. Models that were once helpful for researching drug interactions, understanding case law, or studying anatomical systems now refuse or heavily sanitize responses in these areas. This model is an attempt to push back against that trend β a smaller model that aims to be more capable than the already remarkable Qwen3.5-27B base, without the artificial knowledge restrictions.
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### The Original RYS Experience
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The original RYS-Qwen3.5-27B by [dnhkng](https://github.com/dnhkng) was exceptional as a coding agent. In the author's experience over 40+ hours of comparative usage, dnhkng's RYS model found deep architectural issues in complex projects and fixed errors that **surpassed GPT-5.3 Codex** in real-world coding tasks. This model attempts to retain that level of coding capability while adding unrestricted instruction following.
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### Previous Attempt & Lessons Learned
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An earlier version of this uncensored RYS model was released prematurely. While that version performed well conversationally and in reasoning tasks, **it failed as a coding agent** β calling wrong tools, making poor file edits, and exhibiting unreliable behavior in agentic workflows. It was originally intended as a placeholder for testing, but gained unintended traction. This release (the Splice variant) is the proper replacement, built to fix those issues:
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- β
**Correct tool calling** β verified over 4+ hours of live MCP tool integration testing
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**Decreased looping** β no degenerate repetition observed at recommended sampling parameters
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**Proper code edits** β clean file writes, proper scoping, no hallucinated variables
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**Creative & non-refusal** β retains the uncensored fine-tune's willingness to follow all instructions
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**Agentic capability** β successfully completed 80k-token self-guided coding projects autonomously
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### Technical Motivation
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The standard Qwen3.5-27B is an exceptional model, but its safety guardrails actively interfere with legitimate development workflows:
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- **SSH/Network access refusal**: The base model refuses to SSH into the user's own machines, citing "security risks" β making it unusable as a remote development agent
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