Molmo2

Molmo2 locates objects as points using a text vocabulary.

Tasks
point detection
Sizes
4b, 8b at 378 px
Install
pip install "libreyolo[molmo2]"
Support tier
Sibling tier, since v1.6.0. A separate product surface with its own factory and contract.
Licenses
Code MIT, weights Apache-2.0. Commercial use

Install

bash
pip install "libreyolo[molmo2]"

Predict

Python
from libreyolo import LibreVLM, SAMPLE_IMAGE model = LibreVLM("molmo2-4b", device="cpu")model.set_classes(["person", "building"])result = model(SAMPLE_IMAGE)print(result.points)

set_classes() defines the pointing vocabulary. A custom pointing template must contain {label}. The factory also accepts molmo2-8b and molmo2-o-7b. Training is not supported.

Licensing

Check the license on the Hugging Face repository of the specific weights you download. Every checkpoint in the LibreYOLO org carries one, and they are not always the same across a family. That repository is the authoritative source; the summary below describes what applied when this page was last verified.

This is a description of the licenses involved, not legal advice. If the answer matters commercially, read the licenses yourself and take your own counsel.

Original work
Molmo2, Allen Institute for AI
Upstream license
Apache-2.0
Upstream source
huggingface.co/allenai
LibreYOLO code
MIT
Weights
Apache-2.0, republished at huggingface.co/LibreYOLO
Interpretation
The model publisher declares Apache-2.0.

Verified against LibreYOLO v1.6.0. Support tables, checkpoints and benchmark numbers on this page are generated from the released library and the published weights, not written by hand.