Vehicle Cosine Encoder

256-D embedding model for vehicle re-identification. Trained with CosineEmbeddingLoss on ~5k vehicles from used-car marketplace listings.

Usage

from transformers import AutoModel
model = AutoModel.from_pretrained("quebeccyb/<repo-name>", trust_remote_code=True).eval()
# pixel_values: float tensor (B, 3, 256, 256), letterboxed to square
emb = model(pixel_values)

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Model size

11.3M params

Tensor type

F32

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