Instructions to use hugginglearners/multi-object-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastai
How to use hugginglearners/multi-object-classification with fastai:
from huggingface_hub import from_pretrained_fastai learn = from_pretrained_fastai("hugginglearners/multi-object-classification") - Notebooks
- Google Colab
- Kaggle
| tags: | |
| - fastai | |
| - image-classification | |
| ## Model description | |
| This repo contains the trained model for Multi-object classification | |
| Full credits go to [Nhu Hoang](https://www.linkedin.com/in/nhu-hoang/) | |
| Motivation: Classifying multiple objects is a challenging task without using an object detection algorithm. This model was trained on resnet34 backbone and achieved a good accuracy. | |
| ## Training and evaluation data | |
| ### Training hyperparameters | |
| The following hyperparameters were used during training: | |
| | Hyperparameters | Value | | |
| | :-- | :-- | | |
| | name | Adam | | |
| | learning_rate | 3e-3 | | |
| | training_precision | float16 | | |