Push model using huggingface_hub.

README.md

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 ---
 tags:
-- pytorch
+- model_hub_mixin
+- pytorch_model_hub_mixin
 ---
 
-# CNN Leukemia Classifier
-
-## Model Description
-
-This Convolutional Neural Network (CNN) model is designed for the classification of leukemia images into one of four classes. It was developed for the Quito AI Day event by [Sebastian Sarasti](https://www.linkedin.com/in/sebastiansarasti/). The model leverages a series of convolutional layers followed by fully connected layers to process and classify images effectively.
-
-## Model Architecture
-
-The model consists of the following layers:
-
-- Convolutional Layer: 3 input channels, 128 output channels, 3x3 kernel size, stride 1, padding 1
-- ReLU Activation
-- Max Pooling Layer: 2x2 kernel size
-- Dropout Layer: 0.3 dropout rate
-
-- Convolutional Layer: 128 input channels, 64 output channels, 3x3 kernel size, stride 1, padding 1
-- ReLU Activation
-- Max Pooling Layer: 2x2 kernel size
-- Dropout Layer: 0.3 dropout rate
-
-- Convolutional Layer: 64 input channels, 32 output channels, 3x3 kernel size, stride 1, padding 1
-- ReLU Activation
-- Max Pooling Layer: 2x2 kernel size
-- Dropout Layer: 0.3 dropout rate
-
-- Convolutional Layer: 32 input channels, 8 output channels, 3x3 kernel size, stride 1, padding 1
-- ReLU Activation
-- Max Pooling Layer: 2x2 kernel size
-- Dropout Layer: 0.3 dropout rate
-
-- Flatten Layer
-
-- Fully Connected Layer: 1568 input features, 512 output features
-- ReLU Activation
-- Dropout Layer: 0.5 dropout rate
-
-- Fully Connected Layer: 512 input features, 4 output features
-
-## Dataset
-
-The model was trained on the [Leukemia dataset from Kaggle](https://www.kaggle.com/datasets/mehradaria/leukemia), which consists of images labeled into different leukemia types.
-
-## Usage
-
-To use this model, you can load it from the Hugging Face Hub as follows:
-
-```python
-from transformers import AutoModel
-
-model = AutoModel.from_pretrained("path/to/your/model")
-
+This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration:
+- Library: [More Information Needed]
+- Docs: [More Information Needed]

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