Visual Question Answering
Transformers
Safetensors
English
Chinese
minicpmv
feature-extraction
custom_code
Eval Results
Instructions to use openbmb/MiniCPM-V-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openbmb/MiniCPM-V-2 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "visual-question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("visual-question-answering", model="openbmb/MiniCPM-V-2", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("openbmb/MiniCPM-V-2", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download assets/station.gif from openbmb/MiniCPM-V-2: direct link, hf CLI and curl.
- Browser
- Download file 7.42 MB
-
https://huggingface.co/openbmb/MiniCPM-V-2/resolve/refs%2Fpr%2F28/assets/station.gif
- Command line
-
hf download hf://openbmb/MiniCPM-V-2@refs/pr/28/assets/station.gif
-
curl -L -o station.gif https://huggingface.co/openbmb/MiniCPM-V-2/resolve/refs%2Fpr%2F28/assets/station.gif
7.42 MB

- Xet hash:
- 2125e825e2111be9f207668fe2656301e378cd16029e566bc5a0de5ff2912dbb
- Size of remote file:
- 7.42 MB
- SHA256:
- e7b88efb0040f31992f4069148561d4aeb46ef0cee5e60de4aed4f4be7c3e1be
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