Update README.md

README.md

@@ -1,3 +1,71 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+task_categories:
+- image-classification
+language:
+- en
+tags:
+- Weather
+- Classification
+size_categories:
+- 10K<n<100K
+---
+
+# WeatherNet-05-18039
+
+**Author:** prithivMLmods  
+**License:** Apache 2.0  
+**Modality:** Image  
+**Format:** Parquet  
+**Size:** 10K - 100K samples  
+**Total Rows:** 18,039  
+**Dataset Size:** 544 MB  
+
+## Overview
+
+WeatherNet-05 is a weather image classification dataset consisting of 18,039 images labeled into 5 distinct weather-related classes. The dataset is suitable for training and evaluating computer vision models on the task of classifying weather conditions based on image data.
+
+## Dataset Structure
+
+- **Split:** `train`  
+- **Number of rows:** 18,039  
+- **Label Type:** Categorical (5 classes)  
+- **Image Resolution:** Varies (from 90px to 4.86k px width)  
+- **File Format:** Auto-converted to Parquet for efficient processing
+
+## Label Classes
+
+The dataset contains the following classes (not fully visible in the image but inferred from partial data):
+
+- cloudy or overcast
+- [4 other class names not displayed in the screenshot]
+
+## Usage
+
+You can use the dataset directly with Hugging Face's `datasets` library:
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("prithivMLmods/WeatherNet-05")
+````
+
+## Applications
+
+This dataset is ideal for:
+
+* Weather image classification
+* Transfer learning with visual transformers
+* Fine-tuning pre-trained computer vision models
+
+## Related Models
+
+This dataset has been used to train or fine-tune models such as:
+
+* `prithivMLmods/Weather-Image-Classification` (Image Classification)
+
+## Collections
+
+This dataset is part of the collection:
+
+* `Content Filters SigLIP2/ViT` (Moderation, Balance, Contextual Understanding)