Instructions to use FurAbyss/Cydonia-24B-v4.3-oQ4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use FurAbyss/Cydonia-24B-v4.3-oQ4 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("FurAbyss/Cydonia-24B-v4.3-oQ4") 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
- MLX LM
How to use FurAbyss/Cydonia-24B-v4.3-oQ4 with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "FurAbyss/Cydonia-24B-v4.3-oQ4"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "FurAbyss/Cydonia-24B-v4.3-oQ4" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "FurAbyss/Cydonia-24B-v4.3-oQ4", "messages": [ {"role": "user", "content": "Hello"} ] }'
Cydonia-24B-v4.3-oQ4
This model was quantized from TheDrummer/Cydonia-24B-v4.3 using oQ (oMLX v0.3.12) mixed-precision quantization.
Quantization details
- Model type: mistral small 3.1
- Bits: 4
- Format: MLX safetensors
- Downloads last month
- 100
Model size
4B params
Tensor type
BF16
·
U32 ·
Hardware compatibility
Log In to add your hardware
4-bit
Model tree for FurAbyss/Cydonia-24B-v4.3-oQ4
Base model
mistralai/Mistral-Small-3.1-24B-Base-2503 Finetuned
TheDrummer/Cydonia-24B-v4.3