Image Feature Extraction
Transformers
Safetensors
kanana2_vision_encoder
feature-extraction
vision-encoder
custom_code
Instructions to use kakaocorp/kanana-2-vision-encoder-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kakaocorp/kanana-2-vision-encoder-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="kakaocorp/kanana-2-vision-encoder-tiny", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("kakaocorp/kanana-2-vision-encoder-tiny", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 296 Bytes
df5f3b7 | 1 2 3 4 5 6 7 8 9 10 11 12 13 | {
"auto_map": {
"AutoImageProcessor": "image_processing_kanana2_ve.Kanana2VisionEncoderImageProcessor"
},
"min_pixels": 102400,
"max_pixels": 1638400,
"image_mean": [0.5, 0.5, 0.5],
"image_std": [0.5, 0.5, 0.5],
"patch_size": 16,
"temporal_patch_size": 2,
"merge_size": 2
}
|