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langauge: en
license: mit
tags:
- image-classification
- PyTorch
- VehiclesClassification
- image preprocessing
- Xception
inference: true
datasets:
- AIOmarRehan/Vehicles
spaces:
- AIOmarRehan/CV_Model_Comparison_in_PyTorch
---
## Models Included
This repository provides three different trained PyTorch models for vehicle image classification:
| File Name | Type | Description |
| ----------------------------------------- | --------------------- | ---------------------------------------------------------------------------------------------------------------------- |
| `best_model_finetuned_full.pt` | PyTorch `.pt` | Xception model with **two-phase transfer learning**, fine-tuned on the full dataset. Best generalization and accuracy. |
| `cnn_model_statedict_20260226_034332.pth` | PyTorch `.pth` | **Custom CNN** trained from scratch. Baseline performance, high variance on unseen data. |
| `model.safetensors` | PyTorch `safetensors` | Lightweight **unified CNN model**, faster loading and inference, safe for sharing and reproducible deployment. |
### How to Load
**PyTorch `.pt` or `.pth`:**
```python
import torch
# Load full model
model = torch.load("best_model_finetuned_full.pt")
model.eval()
# Or load CNN state dict
cnn_model = CustomCNN(num_classes=7)
cnn_model.load_state_dict(torch.load("cnn_model_statedict_20260226_034332.pth"))
cnn_model.eval()
```
**Safetensors:**
```python
from safetensors.torch import load_file
state_dict = load_file("model.safetensors")
model.load_state_dict(state_dict)
model.eval()
``` |