| 📌 Teller-v2 — Usage Guide | |
| Teller-v2 is a lightweight experimental language model designed for text generation and small-scale AI research. | |
| This repository contains everything needed to train, finetune, and run inference locally. | |
| 🔧 Requirements | |
| • Python 3.10–3.11 recommended | |
| • PyTorch (CPU or CUDA build) | |
| • Transformers | |
| • tqdm | |
| Install core dependencies: | |
| pip install torch transformers tqdm | |
| 📂 Project Structure | |
| teller_v2p/ | |
| ├─ data/ | |
| │ └─ dataset.txt | |
| ├─ trainteller.py | |
| ├─ generateteller.py | |
| └─ bytetokenizer.py | |
| ✏️ Dataset Format | |
| Place your training text inside: | |
| ./data/dataset.txt | |
| This file should contain plain text. | |
| The model learns directly from this dataset. | |
| The Dataset needs to be like this: | |
| PROMPT: blabla | |
| OUTPUT: blabla | |
| ... | |
| 🚀 Training the Model | |
| Run the training script: | |
| python trainteller.py --epochs [epochs number you want] --batch size [batch size you want] ... | |
| This will: | |
| • load and tokenize dataset | |
| • initialize the model | |
| • train for configured steps | |
| • save weights (e.g., model.pt) | |
| Modify training parameters inside trainteller.py if needed | |
| (such as learning rate, batch size, or number of steps). | |
| 💬 Generating Text | |
| After training, run: | |
| python generateteller.py "your prompt here" | |
| Example: | |
| python generateteller.py "Hello AI," | |
| The script will load model weights and produce continuation text. | |
| 🔁 Tokenizer Notes | |
| The tokenizer used is a simple byte-level tokenizer located in: | |
| bytetokenizer.py | |
| It maps raw bytes to model-usable tokens — ensuring it supports any language or symbol. | |
| 📌 Tips & Customization | |
| • Replace dataset.txt with your own training corpus to create a new model. | |
| • Edit hyperparameters inside train_teller_v25.py to adapt training quality/performance. | |
| • If training stalls or produces low-quality results, try reducing learning rate or training longer. | |
| ⚠️ Disclaimer | |
| Teller-v2 is an experimental project. | |
| It is not intended for production inference without further optimization. | |
| ⭐ Credits | |
| Created by Arthur. | |
| Feel free to extend, redistribute, and improve as long as credits are preserved. |