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AgriMali-EfficientNetV2
Abouba1810/AgriMali-EfficientNetV2
AgriMali-EfficientNetV2 is a machine learning model from Abouba1810. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
AgriMali is an AI-powered agricultural assistant designed to help farmers in Mali 🇲🇱 by providing instant diagnosis for plant diseases.
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Public
Updated May 28, 2026
Repo size
84.3 MB
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.pth84.3 MB · 100%
At a glance
- License
- apache-2.0
- Access
- Public
- Created
- May 28, 2026
- Updated
- May 28, 2026
- SHA
- d34a0efe
Model card
From the Hugging Face model README
AgriMali-EfficientNetV2
AgriMali is an AI-powered agricultural assistant designed to help farmers in Mali 🇲🇱 by providing instant diagnosis for plant diseases.
Overview
This model is based on the EfficientNetV2-S architecture. It has been fine-tuned to classify plant diseases with high accuracy, ensuring robustness and efficiency for mobile-based field applications.
Performance Metrics
The model has been validated on a high-quality dataset, achieving the following results:
| Metric | Value |
|---|---|
| Validation Accuracy | 98.48% |
| Macro F1-Score | 97.99% |
| Macro AUC | 99.98% |
How to use
You can easily load this model in your Python application using the huggingface_hub library:
from huggingface_hub import hf_hub_download
import torch
# Download the model weights
model_path = hf_hub_download(repo_id="Abouba1810/AgriMali-EfficientNetV2", filename="agrimali_best.pth")
# Initialize the model architecture (AgriMaliNet)
model = AgriMaliNet(num_classes=38)
# Load the weights
model.load_state_dict(torch.load(model_path, map_location='cpu'))
model.eval()
- License
- apache-2.0
- Created
- May 28, 2026
- Updated
- May 28, 2026