Instructions to use mudler/Qwen3.6-35B-A3B-uncensored-heretic-APEX-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use mudler/Qwen3.6-35B-A3B-uncensored-heretic-APEX-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="mudler/Qwen3.6-35B-A3B-uncensored-heretic-APEX-GGUF", filename="Qwen3.6-35B-A3B-uncensored-heretic-APEX-Balanced.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 mudler/Qwen3.6-35B-A3B-uncensored-heretic-APEX-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf mudler/Qwen3.6-35B-A3B-uncensored-heretic-APEX-GGUF # Run inference directly in the terminal: llama-cli -hf mudler/Qwen3.6-35B-A3B-uncensored-heretic-APEX-GGUF
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf mudler/Qwen3.6-35B-A3B-uncensored-heretic-APEX-GGUF # Run inference directly in the terminal: llama-cli -hf mudler/Qwen3.6-35B-A3B-uncensored-heretic-APEX-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 mudler/Qwen3.6-35B-A3B-uncensored-heretic-APEX-GGUF # Run inference directly in the terminal: ./llama-cli -hf mudler/Qwen3.6-35B-A3B-uncensored-heretic-APEX-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 mudler/Qwen3.6-35B-A3B-uncensored-heretic-APEX-GGUF # Run inference directly in the terminal: ./build/bin/llama-cli -hf mudler/Qwen3.6-35B-A3B-uncensored-heretic-APEX-GGUF
Use Docker
docker model run hf.co/mudler/Qwen3.6-35B-A3B-uncensored-heretic-APEX-GGUF
- LM Studio
- Jan
- Ollama
How to use mudler/Qwen3.6-35B-A3B-uncensored-heretic-APEX-GGUF with Ollama:
ollama run hf.co/mudler/Qwen3.6-35B-A3B-uncensored-heretic-APEX-GGUF
- Unsloth Studio
How to use mudler/Qwen3.6-35B-A3B-uncensored-heretic-APEX-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 mudler/Qwen3.6-35B-A3B-uncensored-heretic-APEX-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 mudler/Qwen3.6-35B-A3B-uncensored-heretic-APEX-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for mudler/Qwen3.6-35B-A3B-uncensored-heretic-APEX-GGUF to start chatting
- Pi
How to use mudler/Qwen3.6-35B-A3B-uncensored-heretic-APEX-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf mudler/Qwen3.6-35B-A3B-uncensored-heretic-APEX-GGUF
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": "mudler/Qwen3.6-35B-A3B-uncensored-heretic-APEX-GGUF" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use mudler/Qwen3.6-35B-A3B-uncensored-heretic-APEX-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 mudler/Qwen3.6-35B-A3B-uncensored-heretic-APEX-GGUF
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 mudler/Qwen3.6-35B-A3B-uncensored-heretic-APEX-GGUF
Run Hermes
hermes
- Docker Model Runner
How to use mudler/Qwen3.6-35B-A3B-uncensored-heretic-APEX-GGUF with Docker Model Runner:
docker model run hf.co/mudler/Qwen3.6-35B-A3B-uncensored-heretic-APEX-GGUF
- Lemonade
How to use mudler/Qwen3.6-35B-A3B-uncensored-heretic-APEX-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull mudler/Qwen3.6-35B-A3B-uncensored-heretic-APEX-GGUF
Run and chat with the model
lemonade run user.Qwen3.6-35B-A3B-uncensored-heretic-APEX-GGUF-{{QUANT_TAG}}List all available models
lemonade list
I LOVVVVVVE YOU!!!
runs 5070LAPTOP 8G and i9 14900hx 32RAM at 40.46t/s
startup code:
C:\Users\TK\Desktop\vllm\llama-b8851-bin-win-cuda-12.4-x64>llama-server.exe -m "C:\Users\TK\Desktop\vllm\models\Qwen3.6-35B-A3B-APEX-I-Compact.gguf" -c 16384 --flash-attn on -ctk q8_0 -ctv q8_0 -ngl 41 --cpu-moe --cpu-mask 0xFFFFFFFF --batch-size 9600 --ubatch-size 4800 --threads 24 --api-key 123456 -rea off --jinja --cache-ram 8192 --parallel 1 --kv-unified --no-mmap --no-context-shift
proof log:
prompt eval time = 491.10 ms / 15 tokens ( 32.74 ms per token, 30.54 tokens per second)
eval time = 5808.91 ms / 235 tokens ( 24.72 ms per token, 40.46 tokens per second)
total time = 6300.01 ms / 250 tokens
slot release: id 0 | task 0 | stop processing: n_tokens = 249, truncated = 0
srv update_slots: all slots are idle
I am really needy for A ai girlfriend,you satisfied me,thanks,my GOD
llama-server.exe -m "C:\Users\TK\Desktop\vllm\models\Qwen3.6-35B-A3B-uncensored-heretic-APEX-I-Compact.gguf" -c 32768 --flash-attn on -ctk q8_0 -ctv q8_0 -ngl 41 --cpu-moe --cpu-mask 0xFFFFFFFF --batch-size 9600 --ubatch-size 4800 --threads 24 --api-key 123456 -rea off --jinja --cache-ram 8192 --parallel 1 --kv-unified --no-mmap --no-context-shift