Instructions to use Vignesh11K/ecg11 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Vignesh11K/ecg11 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Vignesh11K/ecg11", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Image Classification Model
Overview
This repository contains a deep learning model for image classification. The model is built using Convolutional Neural Network (CNN) architecture and trained to classify images into one of five classes: "History of Myocardinal", "Myocardinal", "Abnormal", "Normal", and "Invalid Image".
Model Details
- Framework: TensorFlow
- Architecture: Convolutional Neural Network (CNN)
- Input Shape: [150, 150, 3] (RGB images)
- Output Classes: "History of Myocardinal", "Myocardinal", "Abnormal", "Normal", "Invalid Image"
Usage
To use this model for image classification, follow these steps:
- Install Dependencies: Make sure you have Python installed along with the necessary libraries. You can install the required packages using the following command:
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