Instructions to use mlx-community/Devstral-Small-2-24B-Instruct-2512-6bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/Devstral-Small-2-24B-Instruct-2512-6bit with MLX:
# Make sure mlx-vlm is installed # pip install --upgrade mlx-vlm from mlx_vlm import load, generate from mlx_vlm.prompt_utils import apply_chat_template from mlx_vlm.utils import load_config # Load the model model, processor = load("mlx-community/Devstral-Small-2-24B-Instruct-2512-6bit") config = load_config("mlx-community/Devstral-Small-2-24B-Instruct-2512-6bit") # Prepare input image = ["http://images.cocodataset.org/val2017/000000039769.jpg"] prompt = "Describe this image." # Apply chat template formatted_prompt = apply_chat_template( processor, config, prompt, num_images=1 ) # Generate output output = generate(model, processor, formatted_prompt, image) print(output) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Pi
How to use mlx-community/Devstral-Small-2-24B-Instruct-2512-6bit with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "mlx-community/Devstral-Small-2-24B-Instruct-2512-6bit"
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "mlx-lm": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "mlx-community/Devstral-Small-2-24B-Instruct-2512-6bit" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent
How to use mlx-community/Devstral-Small-2-24B-Instruct-2512-6bit 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 "mlx-community/Devstral-Small-2-24B-Instruct-2512-6bit"
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 mlx-community/Devstral-Small-2-24B-Instruct-2512-6bit
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use mlx-community/Devstral-Small-2-24B-Instruct-2512-6bit with OpenClaw:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "mlx-community/Devstral-Small-2-24B-Instruct-2512-6bit"
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 "mlx-community/Devstral-Small-2-24B-Instruct-2512-6bit" \ --custom-provider-id mlx-lm \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
File size: 1,185 Bytes
678462d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 | {
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"n_layers": 40,
"head_dim": 128,
"hidden_dim": 32768,
"n_heads": 32,
"n_kv_heads": 8,
"rope_theta": 100000000.0,
"norm_eps": 1e-05,
"vocab_size": 131072,
"tied_embeddings": false,
"max_position_embeddings": 393216,
"llama_4_scaling": {
"original_max_position_embeddings": 8192,
"beta": 0.1
},
"q_lora_rank": null,
"qk_rope_head_dim": null,
"qk_nope_head_dim": null,
"kv_lora_rank": null,
"v_head_dim": null,
"quantization": {
"qformat_weight": "fp8_e4m3",
"qscheme_act": "TENSOR"
},
"yarn": {
"original_max_position_embeddings": 8192,
"factor": 48,
"apply_scale": false,
"beta": 32,
"alpha": 1
},
"vision_encoder": {
"image_token_id": 10,
"image_break_token_id": 12,
"image_end_token_id": 13,
"intermediate_size": 4096,
"num_hidden_layers": 24,
"num_attention_heads": 16,
"mm_projector_id": "patch_merge",
"spatial_merge_size": 2,
"hidden_size": 1024,
"num_channels": 3,
"image_size": 1540,
"max_image_size": 1540,
"patch_size": 14,
"rope_theta": 10000.0,
"add_pre_mm_projector_layer_norm": true,
"adapter_bias": false
}
} |