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
feat: test upload - Trendyol DinoV2 Product Similarity and Retrieval Embedding Model
7bc81ce verified | { | |
| "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" | |
| ] | |
| } |