Any-to-Any
Transformers
ONNX
Safetensors
minicpmo
feature-extraction
minicpm-o
minicpm-v
multimodal
full-duplex
custom_code
Instructions to use rycerzes/MiniCPM-o-4_5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rycerzes/MiniCPM-o-4_5 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("rycerzes/MiniCPM-o-4_5", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 842 Bytes
2e894b4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 | {
"image_processor_type": "MiniCPMVImageProcessor",
"feature_extractor_type": "MiniCPMAAudioProcessor",
"auto_map": {
"AutoProcessor": "processing_minicpmo.MiniCPMOProcessor",
"AutoImageProcessor": "processing_minicpmo.MiniCPMVImageProcessor",
"AutoFeatureExtractor": "processing_minicpmo.MiniCPMAAudioProcessor"
},
"processor_class": "MiniCPMOProcessor",
"max_slice_nums": 9,
"scale_resolution": 448,
"patch_size": 14,
"use_image_id": true,
"image_feature_size": 64,
"im_start": "<image>",
"im_end": "</image>",
"slice_start": "<slice>",
"slice_end": "</slice>",
"unk": "<unk>",
"im_id_start": "<image_id>",
"im_id_end": "</image_id>",
"slice_mode": true,
"audio_pool_step": 5,
"norm_mean": [
0.5,
0.5,
0.5
],
"norm_std": [
0.5,
0.5,
0.5
],
"version": 4.5
} |