Instructions to use khalid99ml/bangladeshi-taka-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use khalid99ml/bangladeshi-taka-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="khalid99ml/bangladeshi-taka-classifier") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("khalid99ml/bangladeshi-taka-classifier") model = AutoModelForImageClassification.from_pretrained("khalid99ml/bangladeshi-taka-classifier") - Notebooks
- Google Colab
- Kaggle
π§π© Bangladeshi Taka Banknote Classifier
This model is an image classifier that recognizes the denomination of Bangladeshi banknotes (paper currency).
It was fine-tuned on the Jakir057/bangladeshi_banknotes_70k dataset using EfficientNet-B0 as the backbone.
π Model Details
| Model Architecture | EfficientNet-B0 |
| Fine-tuned From | google/efficientnet-b0 |
| Dataset | Jakir057/bangladeshi_banknotes_70k |
| Number of Classes | 8 (2, 5, 10, 20, 50, 100, 500, 1000 Taka) |
| Input | Banknote image (RGB, clear view of the note) |
| License | Apache 2.0 |
π Quick Start
from transformers import pipeline
from PIL import Image
pipe = pipeline("image-classification", model="your-username/bangladeshi-taka-classifier")
img = Image.open("path/to/your_note.jpg")
result = pipe(img)
print(result)
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