Image-Text-to-Text
MLX
Safetensors
English
molmo_point
multimodal
olmo
molmo
molmo2
conversational
custom_code
4-bit precision
Instructions to use mlx-community/MolmoPoint-8B-nvfp4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/MolmoPoint-8B-nvfp4 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/MolmoPoint-8B-nvfp4") config = load_config("mlx-community/MolmoPoint-8B-nvfp4") # 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
- LM Studio
| { | |
| "auto_map": { | |
| "AutoProcessor": "processing_molmo2.Molmo2Processor" | |
| }, | |
| "image_use_col_tokens": true, | |
| "processor_class": "Molmo2Processor", | |
| "use_frame_special_tokens": true, | |
| "use_low_res_token_for_global_crops": true, | |
| "use_single_crop_col_tokens": false, | |
| "use_single_crop_start_token": true, | |
| "video_use_col_tokens": false | |
| } | |