Visual Question Answering
Transformers
PyTorch
English
minicpmv
feature-extraction
GUI
Agent
minicpm
custom_code
Instructions to use RhapsodyAI/minicpm-guidance with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RhapsodyAI/minicpm-guidance 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="RhapsodyAI/minicpm-guidance", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("RhapsodyAI/minicpm-guidance", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 481 Bytes
8833898 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | {
"auto_map": {
"AutoImageProcessor": "processing_minicpmv.MiniCPMVImageProcessor",
"AutoProcessor": "processing_minicpmv.MiniCPMVProcessor"
},
"image_processor_type": "MiniCPMVImageProcessor",
"processor_class": "MiniCPMVProcessor",
"query_num": 64,
"max_slice_nums": 9,
"scale_resolution": 448,
"patch_size": 14,
"max_inp_length": 2048,
"image_mean": [
0.5,
0.5,
0.5
],
"image_std": [
0.5,
0.5,
0.5
]
}
|