Image Feature Extraction
Transformers
Safetensors
vehicle_encoder
feature-extraction
vehicle
metric-learning
image-embedding
custom_code
Instructions to use quebeccyb/vehitv-cropped with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use quebeccyb/vehitv-cropped with Transformers:
# 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)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("quebeccyb/vehitv-cropped", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "VehicleEncoderModel" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "configuration_vehicle_encoder.VehicleEncoderConfig", | |
| "AutoModel": "modeling_vehicle_encoder.VehicleEncoderModel" | |
| }, | |
| "blocks_per_stage": 2, | |
| "dtype": "float32", | |
| "img_size": 256, | |
| "latent_dim": 256, | |
| "model_type": "vehicle_encoder", | |
| "transformers_version": "5.12.0" | |
| } | |