Image Classification
Transformers
TensorBoard
Safetensors
timm_wrapper
vision
Generated from Trainer
Instructions to use davanstrien/test-timm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use davanstrien/test-timm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="davanstrien/test-timm") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("davanstrien/test-timm") model = AutoModelForImageClassification.from_pretrained("davanstrien/test-timm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,006 Bytes
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"architecture": "mobilenetv3_large_100",
"data_config": {
"crop_mode": "center",
"crop_pct": 0.875,
"input_size": [
3,
224,
224
],
"interpolation": "bilinear",
"mean": [
0.0,
0.0,
0.0
],
"std": [
1.0,
1.0,
1.0
]
},
"image_processor_type": "TimmWrapperImageProcessor",
"num_classes": 11221,
"num_features": 1280,
"pretrained_cfg": {
"classifier": "classifier",
"crop_mode": "center",
"crop_pct": 0.875,
"custom_load": false,
"first_conv": "conv_stem",
"fixed_input_size": false,
"input_size": [
3,
224,
224
],
"interpolation": "bilinear",
"mean": [
0.0,
0.0,
0.0
],
"num_classes": 11221,
"origin_url": "https://github.com/Alibaba-MIIL/ImageNet21K",
"paper_ids": "arXiv:2104.10972v4",
"pool_size": [
7,
7
],
"std": [
1.0,
1.0,
1.0
],
"tag": "miil_in21k"
}
}
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