Instructions to use mlx-community/Inkling-Small-mxfp4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/Inkling-Small-mxfp4 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/Inkling-Small-mxfp4") config = load_config("mlx-community/Inkling-Small-mxfp4") # 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/Inkling-Small-mxfp4 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/Inkling-Small-mxfp4"
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": "mlx-community/Inkling-Small-mxfp4" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use mlx-community/Inkling-Small-mxfp4 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/Inkling-Small-mxfp4"
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/Inkling-Small-mxfp4
Run Hermes
hermes
- OpenClaw new
How to use mlx-community/Inkling-Small-mxfp4 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/Inkling-Small-mxfp4"
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/Inkling-Small-mxfp4" \ --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"
Update README.md
#1
by pcuenq HF Staff - opened
README.md
CHANGED
|
@@ -2,6 +2,29 @@
|
|
| 2 |
language: en
|
| 3 |
library_name: mlx
|
| 4 |
pipeline_tag: image-text-to-text
|
|
|
|
| 5 |
tags:
|
| 6 |
- mlx
|
| 7 |
---
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 2 |
language: en
|
| 3 |
library_name: mlx
|
| 4 |
pipeline_tag: image-text-to-text
|
| 5 |
+
base_model: thinkingmachines/Inkling-Small
|
| 6 |
tags:
|
| 7 |
- mlx
|
| 8 |
---
|
| 9 |
+
|
| 10 |
+
# Inkling Small MXFP4
|
| 11 |
+
|
| 12 |
+
MXFP4 version of [thinkingmachines/Inkling-Small](https://huggingface.co/thinkingmachines/Inkling-Small).
|
| 13 |
+
|
| 14 |
+
This checkpoint uses less memory than [thinkingmachines/Inkling-Small-NVFP4](https://huggingface.co/thinkingmachines/Inkling-Small-NVFP4),
|
| 15 |
+
but quantizes more tensors to MXFP4. The official NVFP4 checkpoint, on the other hand, only applies 4-bit quantization to routed experts,
|
| 16 |
+
so quality should be better.
|
| 17 |
+
|
| 18 |
+
For the best quality, please run the official NVFP4 checkpoint directly with MLX, there's no need to convert:
|
| 19 |
+
|
| 20 |
+
```bash
|
| 21 |
+
mlx_vlm.generate --prompt "who are you?" --model thinkingmachines/Inkling-Small-NVFP4
|
| 22 |
+
```
|
| 23 |
+
|
| 24 |
+
Or, if you want to try the version in this repo (lower memory consumption, faster):
|
| 25 |
+
|
| 26 |
+
```bash
|
| 27 |
+
mlx_vlm.generate --prompt "who are you?" --model mlx-community/Inkling-Small-mxfp4
|
| 28 |
+
```
|
| 29 |
+
|
| 30 |
+
**Note**: please make sure you use the Inkling Small mlx-vlm PR.
|