Instructions to use openbmb/MiniCPM-V with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openbmb/MiniCPM-V with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="openbmb/MiniCPM-V", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("openbmb/MiniCPM-V", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- d609b4cc6a1ba0438e2efc70fa74e622dc046319841cf1f8b3b0c01e9396fa96
- Size of remote file:
- 2.5 MB
- SHA256:
- 6118fbac6bec46c54f2cded08bc8ccf9411cdee580d384b70908faee49a368e7
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