Update README.md

README.md

@@ -1,6 +1,90 @@
 ---
 license: apache-2.0
 pipeline_tag: tabular-classification
-tags:
-- not-for-all-audiences
----
+---
+# NexaAstro: Stellar Classification with SDSS Data
+
+**NexaAstro - Stellar Classification** is a hybrid machine learning model for classifying stars using data from the Sloan Digital Sky Survey (SDSS). It leverages a two-stage architecture:
+
+- **CatBoost**: Gradient boosting for robust feature modeling.
+- **Feedforward Neural Network (NN)**: Refines predictions for enhanced accuracy.
+
+This model is part of the [Nexa Scientific Model Suite](https://huggingface.co/spaces/Allanatrix/NexaHub), dedicated to advancing scientific discovery through machine learning.
+
+---
+
+## Model Overview
+
+- **Task**: Multi-class stellar classification (e.g., Main Sequence, White Dwarf, Giant).
+- **Input**: SDSS stellar attributes (u, g, r, i, z magnitudes, spectral lines, etc.).
+- **Output**: Predicted stellar class label.
+- **Architecture**: CatBoost for feature extraction, followed by a Feedforward Neural Network for classification.
+
+---
+
+## Applications
+
+- **Stellar Population Studies**: Analyzing distributions and characteristics of stellar types.
+- **Galaxy Classification Support**: Providing stellar data for broader galactic studies.
+- **Astrophysics Education**: Enabling interactive learning and research tools.
+- **Feature Engineering**: Supporting advanced astronomical machine learning workflows.
+
+---
+
+## Getting Started
+
+### Example Usage
+```python
+import joblib
+import torch
+import numpy as np
+from my_nn_model import StellarNN  # Replace with actual neural network module
+
+# Load CatBoost model
+catboost_model = joblib.load("Allanatrix/catboost_model.pkl")
+
+# Load PyTorch neural network model
+nn_model = StellarNN()
+nn_model.load_state_dict(torch.load("Allanatrix/stellar_nn.pt"))
+nn_model.eval()
+
+# Example prediction with SDSS features
+features = np.array([...])  # SDSS input features (e.g., magnitudes, spectral data)
+catboost_out = catboost_model.predict(features)
+refined_pred = nn_model(torch.tensor(catboost_out).float())
+```
+
+Refer to the model documentation for detailed preprocessing and input requirements.
+
+---
+
+## Dataset
+
+- **Source**: [Sloan Digital Sky Survey (SDSS)](https://www.sdss.org/).
+- **Preprocessing**: Data cleaned, normalized, and filtered by magnitude thresholds.
+- **Labels**: Discrete stellar class labels derived from expert annotations.
+
+---
+
+## Citation and License
+
+If you use NexaAstro in your research, please cite this repository and acknowledge the SDSS dataset.  
+The model and associated code are licensed under the **Boost Software License 1.1 (BSL-1.1)**.
+
+---
+
+## Part of the Nexa Scientific Ecosystem
+
+Explore related tools and models in the Nexa ecosystem:
+- [Nexa Data Studio](https://huggingface.co/spaces/Allanatrix/NexaDataStudio): Tools for data processing and visualization.
+- [Nexa R&D](https://huggingface.co/spaces/Allanatrix/NexaR&D): Research-focused model development environment.
+- [Nexa Infrastructure](https://huggingface.co/spaces/Allanatrix/NexaInfrastructure): Scalable ML deployment solutions.
+- [Nexa Hub](https://huggingface.co/spaces/Allanatrix/NexaHub): Central portal for Nexa resources.
+
+*Coming Soon:*
+- Galaxy Morphology Classifier
+- Exoplanet Transit Detection Model
+
+---
+
+*Developed and maintained by [Allan](https://huggingface.co/Allanatrix), an independent machine learning researcher specializing in astrophysical and scientific AI systems.*