A high-performance language model architecture.
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## Overview
**ChatGCLM** is a generative language model that deviates from the traditional Transformer architecture by utilizing a hybrid approach of **Local** and **Global Convolutions**. By leveraging Fast Fourier Transforms (FFT) for global context, ChatGCLM achieves a massive receptive field with a fraction of the computational overhead associated with standard attention mechanisms.
The architecture is designed for efficiency, speed, and high-quality generation, featuring a custom vocabulary reduction system that optimizes the embedding space for specific datasets.
## 📦 Installation
Download this repository and extract it.
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## Usage
### 1. Training the Model
Place your `.txt` data files in the `data/` directory and run:
```bash
python train_chatgclm.py
```
This script will build the vocabulary and train the foundation model
### 2. Sample from the model
Run sample.py to generate text with the model
```bash
python sample.py
```
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## Fine-tuning
You may fine-tune the model by resuming training from a checkpoint, you may use a different dataset, you may also change parameters such as the learning rate, batch size, etc.
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