docs: update docs

Author: micedre

docs/source/api.rst

@@ -35,7 +35,15 @@ FastText Classifier
 Configuration and Factory
 ~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-.. automodule:: torchTextClassifiers.classifiers.fasttext.fasttext
+.. automodule:: torchTextClassifiers.classifiers.fasttext.core
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+Wrapper Interface
+~~~~~~~~~~~~~~~~~
+
+.. automodule:: torchTextClassifiers.classifiers.fasttext.wrapper
    :members:
    :undoc-members:
    :show-inheritance:

docs/source/index.rst

@@ -1,7 +1,7 @@
-torchTextClassifiers Documentation
+**torchTextClassifiers** Documentation
 ====================================
 
-Welcome to torchTextClassifiers, a unified framework for text classification with PyTorch Lightning integration.
+Welcome to **torchTextClassifiers**, a unified framework for text classification with PyTorch Lightning integration.
 
 .. image:: https://img.shields.io/badge/python-3.8%2B-blue.svg
    :target: https://python.org
@@ -18,17 +18,18 @@ Welcome to torchTextClassifiers, a unified framework for text classification wit
 Overview
 --------
 
-torchTextClassifiers provides a comprehensive, extensible framework for building and training
+**torchTextClassifiers** provides a comprehensive, extensible framework for building and training
 text classification models. It offers a unified API that abstracts away the complexity
 of different model architectures while providing flexibility for advanced users.
 
 🚀 **Key Features:**
 
 * **Unified API**: Consistent interface across different model types
 * **PyTorch Lightning Integration**: Production-ready training with automatic GPU handling
-* **FastText Implementation**: Fast and efficient text classification
 * **Mixed Features Support**: Handle both text and categorical data
 * **Extensible Architecture**: Easy to add new model types
+* **Explainability**: Add explainability support (depends on classifier types)
+
 
 Quick Start
 -----------

docs/source/installation.rst

@@ -21,14 +21,9 @@ Core dependencies that will be automatically installed:
 - PyTorch >= 1.9.0
 - PyTorch Lightning >= 1.6.0
 - NumPy >= 1.19.0
-- Pandas >= 1.3.0
-- scikit-learn >= 1.0.0
 
 Optional dependencies for enhanced functionality:
 
-- Jupyter >= 1.0.0 (for notebook examples)
-- Matplotlib >= 3.3.0 (for visualization)
-- Seaborn >= 0.11.0 (for plotting)
 
 Installation Methods
 --------------------