Instructions to use thoddnn/d3-mini-q4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use thoddnn/d3-mini-q4 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("thoddnn/d3-mini-q4") config = load_config("thoddnn/d3-mini-q4") # 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 thoddnn/d3-mini-q4 with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "thoddnn/d3-mini-q4"
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": "thoddnn/d3-mini-q4" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent
How to use thoddnn/d3-mini-q4 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 "thoddnn/d3-mini-q4"
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 thoddnn/d3-mini-q4
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use thoddnn/d3-mini-q4 with OpenClaw:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "thoddnn/d3-mini-q4"
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 "thoddnn/d3-mini-q4" \ --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"
Download fenn_d3.json from thoddnn/d3-mini-q4: direct link, hf CLI and curl.
- Browser
- Download file 1.33 kB
-
https://huggingface.co/thoddnn/d3-mini-q4/resolve/main/fenn_d3.json
- Command line
-
hf download hf://thoddnn/d3-mini-q4/fenn_d3.json
-
curl -L -o fenn_d3.json https://huggingface.co/thoddnn/d3-mini-q4/resolve/main/fenn_d3.json
1.33 kB
| { | |
| "model_id": "vllm-sr/d3-mini", | |
| "revision": "a475367de0d8133a3c1a2a0dc12303d89cfa2ab4", | |
| "bits": 4, | |
| "group_size": 64, | |
| "precise_norms": true, | |
| "vision_dtype": "bfloat16", | |
| "readout_dtype": "float32", | |
| "files": { | |
| "LICENSE": "c71d239df91726fc519c6eb72d318ec65820627232b2f796219e87dcf35d0ab4", | |
| "tokenizer_config.json": "316230d6a809701f4db5ea8f8fc862bc3a6f3229c937c174e674ff3ca0a64ac8", | |
| "weights.safetensors": "e6ba69abc5ba997f6fc041721e00c6ebb922ad5fd2efa1449f50359318bb0bfb", | |
| "config.json": "8f5f404a71ecc53c4ff26fc42cb4c778ffacfb4c9623f5e2d51245166d6b5057", | |
| "tokenizer.json": "5f9e4d4901a92b997e463c1f46055088b6cca5ca61a6522d1b9f64c4bb81cb42", | |
| "NOTICE": "1b1c0d9508ca9703a5f7eabfc70800676e167ad1de1e72ac69f4b9cab1b9272b", | |
| "merges.txt": "a9d356d7bdf1ef4949e3e748e95b8e10ad9d4e2e838eddc38a0a7b6b94d1db8d", | |
| "chat_template.jinja": "a4aee8afcf2e0711942cf848899be66016f8d14a889ff9ede07bca099c28f715", | |
| "decision_config.json": "588bc0ac7644479b9adde0498d80b6fb7c576388992564ac67599c05d29add07", | |
| "vocab.json": "ce99b4cb2983d118806ce0a8b777a35b093e2000a503ebde25853284c9dfa003", | |
| "video_preprocessor_config.json": "7768af27c1fafa9cc9011c1dc20067e03f8915e03b63504550e11d5066986d13", | |
| "preprocessor_config.json": "27225450ac9c6529872ee1924fcb0962ff5634834f817040f444118116f4e516" | |
| } | |
| } | |