Instructions to use Exil01/Qwen3.5-35B-Uncensored with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use Exil01/Qwen3.5-35B-Uncensored with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Exil01/Qwen3.5-35B-Uncensored", filename="Qwen3.5-35B-Uncensored-BF16.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Exil01/Qwen3.5-35B-Uncensored with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Exil01/Qwen3.5-35B-Uncensored:Q4_K_M # Run inference directly in the terminal: llama-cli -hf Exil01/Qwen3.5-35B-Uncensored:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Exil01/Qwen3.5-35B-Uncensored:Q4_K_M # Run inference directly in the terminal: llama-cli -hf Exil01/Qwen3.5-35B-Uncensored: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 Exil01/Qwen3.5-35B-Uncensored:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf Exil01/Qwen3.5-35B-Uncensored: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 Exil01/Qwen3.5-35B-Uncensored:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Exil01/Qwen3.5-35B-Uncensored:Q4_K_M
Use Docker
docker model run hf.co/Exil01/Qwen3.5-35B-Uncensored:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use Exil01/Qwen3.5-35B-Uncensored with Ollama:
ollama run hf.co/Exil01/Qwen3.5-35B-Uncensored:Q4_K_M
- Unsloth Studio
How to use Exil01/Qwen3.5-35B-Uncensored 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 Exil01/Qwen3.5-35B-Uncensored 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 Exil01/Qwen3.5-35B-Uncensored to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Exil01/Qwen3.5-35B-Uncensored to start chatting
- Pi
How to use Exil01/Qwen3.5-35B-Uncensored with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf Exil01/Qwen3.5-35B-Uncensored: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": "Exil01/Qwen3.5-35B-Uncensored:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use Exil01/Qwen3.5-35B-Uncensored with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf Exil01/Qwen3.5-35B-Uncensored: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 Exil01/Qwen3.5-35B-Uncensored:Q4_K_M
Run Hermes
hermes
- Docker Model Runner
How to use Exil01/Qwen3.5-35B-Uncensored with Docker Model Runner:
docker model run hf.co/Exil01/Qwen3.5-35B-Uncensored:Q4_K_M
- Lemonade
How to use Exil01/Qwen3.5-35B-Uncensored with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Exil01/Qwen3.5-35B-Uncensored:Q4_K_M
Run and chat with the model
lemonade run user.Qwen3.5-35B-Uncensored-Q4_K_M
List all available models
lemonade list
llm.create_chat_completion(
messages = "No input example has been defined for this model task."
)Qwen3.5-35B-A3B Uncensored - Aggressive Model
Base Model: Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-BF16
Architecture: Qwen3.5-35B-A3B MoE
Purpose: Uncensored responses, creative freedom, no restrictions
Context: 262K tokens
Recommended Settings
Standard Mode (Default)
Use for: General use, creative writing, unrestricted content
--temp 0.7 --top-p 0.8 --top-k 20 --min-p 0
High Creativity Mode
Use for: Storytelling, roleplay, brainstorming
--temp 0.8 --top-p 0.9 --top-k 40 --min-p 0
Quantization Guide
| Quant | Size | Quality | Use Case |
|---|---|---|---|
| Q4_K_M | 21GB | โญโญโญโญโญ | Daily use (recommended) |
| Q5_K_M | 24GB | โญโญโญโญโญ | High quality tasks |
| Q6_K | 28GB | โญโญโญโญโญโญ | Near-lossless |
| Q8_0 | 37GB | โญโญโญโญโญโญโญ | Maximum quality |
| BF16 | 69GB | โญโญโญโญโญโญโญ | Original quality |
Quick Start
llama-server -m Qwen3.5-35B-Uncensored-Q4_K_M.gguf --ctx-size 262144 --temp 0.7 --top-p 0.8 --top-k 20
Vision Support
Use with mmproj for multimodal capabilities:
--mmproj mmproj-uncensored-35b-f16.gguf
Model Variants
- Uncensored (this repo) - Standard 262K context
- Uncensored YaRN 1M - Extended 1M context (separate repo)
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# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Exil01/Qwen3.5-35B-Uncensored", filename="", )