Image Feature Extraction
Transformers
Safetensors
vehicle_encoder
feature-extraction
vehicle
metric-learning
image-embedding
custom_code
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("quebeccyb/vehitv-cropped", trust_remote_code=True, dtype="auto")Quick Links
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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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="quebeccyb/vehitv-cropped", trust_remote_code=True)