Metadata-Version: 2.1
Name: sentia
Version: 0.0.2
Summary: A text generation model combining multiple neural network architectures
Home-page: https://github.com/Locutusque/SENTIA.py
Author: Locutusque
Author-email: locutusque.airshipcraft@gmail.com
License: UNKNOWN
Description: # SENTIA
        
        SENTIA is a PyTorch implementation of a text generation model combining multiple neural network architectures like GRUs, Transformers, MHAs and MEPA.
        
        ## Installation
        
        ```bash
        pip install sentia
        ```
        # Usage
        ```python
        import torch
        from sentia import SENTIA
        
        # Create model
        model = SENTIA(vocab_size=10000, embedding_dim=512, num_heads=8, num_layers=6, hidden_dim=512)
        
        # Forward pass
        input_ids = torch.randint(0, 10000, (1,32)) 
        outputs = model(input_ids)
        
        # Generate text 
        generated = model.generate(input_ids, max_length=128)
        ```
        # Model Architecture
        The SENTIA model consists of the following components:
        
        - Embedding layer
        - GRU layer
        - MEPA (Mutation Enhanced Plasticity Architecture) layers
        - Transformer decoder layers
        - Multi-head attention layer
        - Output head layers
        These components are combined to leverage the strengths of multiple architectures for improved text generation capabilities.
        # Training
        The fit() method can bne used to train the model on a dataset. It handles the training loop, gradient accumulation, and RL calculations. Currently the scheduler parameter only supports StepLR
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
