Any-to-Any
Transformers
ONNX
Safetensors
minicpmo
feature-extraction
minicpm-o
minicpm-v
multimodal
full-duplex
custom_code
Eval Results
Instructions to use openbmb/MiniCPM-o-4_5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openbmb/MiniCPM-o-4_5 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("openbmb/MiniCPM-o-4_5", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Add OmniCompass evaluation results
#24
by VCLab-PolyU - opened
Add the OmniCompass benchmark authors' published results for MiniCPM-o-4.5-8B on omnicompass_av. Each value is Overall Cross-Specification Consistency Score on a 0-100 scale; higher is better.
Source: https://omnicompass.netlify.app/#leaderboard
Benchmark: https://huggingface.co/datasets/VCLab-PolyU/OmniCompass
The YAML preserves the published one-decimal scores and records frame counts and source attribution. It adds evaluation metadata only and makes no HF verified claim.