Feature Extraction
Transformers
PyTorch
Safetensors
English
trendyol_dinov2
image-similarity
image-retrieval
computer-vision
e-commerce
dinov2
custom_code
Eval Results (legacy)
Instructions to use Trendyol/trendyol-dino-v2-ecommerce-256d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Trendyol/trendyol-dino-v2-ecommerce-256d with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Trendyol/trendyol-dino-v2-ecommerce-256d", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Trendyol/trendyol-dino-v2-ecommerce-256d", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 800 Bytes
a15fec5 7bc81ce a15fec5 | 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 36 37 38 39 40 41 42 43 | {
"image_processor_type": "TrendyolDinoV2ImageProcessor",
"processor_class": "TrendyolDinoV2ImageProcessor",
"auto_map": {
"AutoImageProcessor": "image_processing_trendyol_dinov2.TrendyolDinoV2ImageProcessor"
},
"input_size": 224,
"downscale_size": 332,
"pad_color": 255,
"jpeg_quality": 90,
"do_normalize": true,
"image_mean": [
0.485,
0.456,
0.406
],
"image_std": [
0.229,
0.224,
0.225
],
"do_resize": true,
"size": {
"height": 224,
"width": 224
},
"resample": 3,
"do_center_crop": false,
"crop_size": {
"height": 224,
"width": 224
},
"do_convert_rgb": true,
"transforms": [
"DownScaleLanczos",
"JPEGCompression",
"ScaleImage",
"PadToSquare",
"Resize",
"ToTensor",
"Normalize"
]
} |