Image Feature Extraction
Transformers
Safetensors
mimo26_vision
feature-extraction
vision
mimo
custom_code
Instructions to use immanuelpeter/MiMoViT-2.6-Flash with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use immanuelpeter/MiMoViT-2.6-Flash with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="immanuelpeter/MiMoViT-2.6-Flash", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("immanuelpeter/MiMoViT-2.6-Flash", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 320 Bytes
2880544 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | {
"min_pixels": 8192,
"max_pixels": 8388608,
"patch_size": 16,
"temporal_patch_size": 2,
"merge_size": 2,
"image_mean": [
0.485,
0.456,
0.406
],
"image_std": [
0.229,
0.224,
0.225
],
"image_processor_type": "Qwen2VLImageProcessor",
"processor_class": "AutoImageProcessor"
}
|