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 from transformers import pipeline pipe = pipeline("visual-question-answering", model="openbmb/MiniCPM-V-2", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("openbmb/MiniCPM-V-2", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Conditional chatting
#10
by paulorodriguesjr - opened
Hi guys,
Can i use this model to have an efficient conditional chatting like:
- If there is a red car OR black car OR yellow car in the image give me some details of image, otherwise, just answer 'NO'.
I have tested some phrases like this, but 99% of time it gives me 'NO', even if the image have the colored cars mentioned in the prompt.
I think you can make it into 2 stages.
- yes or no
- if yes then captioning