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
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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 |
|