Image-Text-to-Text
MLX
Safetensors
English
molmo_point
multimodal
olmo
molmo
molmo2
conversational
custom_code
5-bit
Instructions to use mlx-community/MolmoPoint-8B-5bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/MolmoPoint-8B-5bit 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-5bit") config = load_config("mlx-community/MolmoPoint-8B-5bit") # 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
File size: 679 Bytes
4c1133d | 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 | ---
license: apache-2.0
language:
- en
base_model:
- Qwen/Qwen3-8B
- google/siglip-so400m-patch14-384
pipeline_tag: image-text-to-text
tags:
- multimodal
- olmo
- molmo
- molmo2
- molmo_point
- mlx
---
# mlx-community/MolmoPoint-8B-5bit
This model was converted to MLX format from [`allenai/MolmoPoint-8B`]() using mlx-vlm version **0.4.1**.
Refer to the [original model card](https://huggingface.co/allenai/MolmoPoint-8B) for more details on the model.
## Use with mlx
```bash
pip install -U mlx-vlm
```
```bash
python -m mlx_vlm.generate --model mlx-community/MolmoPoint-8B-5bit --max-tokens 100 --temperature 0.0 --prompt "Describe this image." --image <path_to_image>
```
|