Instructions to use RepublicOfKorokke/Qwen3.5-0.8B-oQ8-fp16-lm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use RepublicOfKorokke/Qwen3.5-0.8B-oQ8-fp16-lm with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("RepublicOfKorokke/Qwen3.5-0.8B-oQ8-fp16-lm") prompt = "Write a story about Einstein" messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, add_generation_prompt=True ) text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Pi
How to use RepublicOfKorokke/Qwen3.5-0.8B-oQ8-fp16-lm with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "RepublicOfKorokke/Qwen3.5-0.8B-oQ8-fp16-lm"
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "mlx-lm": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "RepublicOfKorokke/Qwen3.5-0.8B-oQ8-fp16-lm" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use RepublicOfKorokke/Qwen3.5-0.8B-oQ8-fp16-lm with Hermes Agent:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "RepublicOfKorokke/Qwen3.5-0.8B-oQ8-fp16-lm"
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 RepublicOfKorokke/Qwen3.5-0.8B-oQ8-fp16-lm
Run Hermes
hermes
- MLX LM
How to use RepublicOfKorokke/Qwen3.5-0.8B-oQ8-fp16-lm with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "RepublicOfKorokke/Qwen3.5-0.8B-oQ8-fp16-lm"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "RepublicOfKorokke/Qwen3.5-0.8B-oQ8-fp16-lm" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "RepublicOfKorokke/Qwen3.5-0.8B-oQ8-fp16-lm", "messages": [ {"role": "user", "content": "Hello"} ] }'
How to use from
PiConfigure the model in Pi
# Install Pi:
npm install -g @mariozechner/pi-coding-agent# Add to ~/.pi/agent/models.json:
{
"providers": {
"mlx-lm": {
"baseUrl": "http://localhost:8080/v1",
"api": "openai-completions",
"apiKey": "none",
"models": [
{
"id": "RepublicOfKorokke/Qwen3.5-0.8B-oQ8-fp16-lm"
}
]
}
}
}Run Pi
# Start Pi in your project directory:
piQuick Links
THIS MODEL IS NOT MULTI MODAL
Qwen3.5-0.8B-oQ8
This model was quantized using oQ mixed-precision quantization.
float16 gives ~20% faster prefill on M1/M2 Apple Silicon (native fp16). bfloat16 is safer on M3/M4 and for numerical stability.
Quantization details
- Model type: qwen3_5
- Bits: 8
- Group size: 64
- Format: MLX safetensors
- Downloads last month
- 21
Model size
0.2B params
Tensor type
F16
·
U32 ·
Hardware compatibility
Log In to add your hardware
8-bit
Start the MLX server
# Install MLX LM: uv tool install mlx-lm# Start a local OpenAI-compatible server: mlx_lm.server --model "RepublicOfKorokke/Qwen3.5-0.8B-oQ8-fp16-lm"