Any-to-Any
Transformers
Safetensors
multilingual
minicpmo
feature-extraction
minicpm-o
omni
vision
ocr
multi-image
video
custom_code
audio
speech
voice cloning
live Streaming
realtime speech conversation
asr
tts
4-bit precision
gptq
Instructions to use openbmb/MiniCPM-o-2_6-int4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openbmb/MiniCPM-o-2_6-int4 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("openbmb/MiniCPM-o-2_6-int4", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Add license, paper link, GitHub, and project page to model card
#8
by nielsr HF Staff - opened
This PR enhances the model card for openbmb/MiniCPM-o-2_6-int4 by:
- Adding the
license: apache-2.0to the metadata block, as indicated in the official GitHub repository. - Including a direct link to the associated research paper: MiniCPM-V 4.5: Cooking Efficient MLLMs via Architecture, Data, and Training Recipe.
- Providing a link to the main GitHub repository: https://github.com/OpenBMB/MiniCPM-V.
- Adding a link to the project's online demo/project page: https://minicpm-omni-webdemo-us.modelbest.cn/.
These additions improve the completeness and discoverability of information about the model for users and researchers.
tc-mb changed pull request status to merged