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
a15fec5 verified - Xet hash:
- dd849b6166392f9bfd65627feb84d2e900441b78cc570bfd2dc3cf91ff868fdc
- Size of remote file:
- 548 MB
- SHA256:
- 60a38364dc18e4dd31a5bda0e8c36223a9b3518112ceeee7650ef59fd072a6cd
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