Instructions to use ducklin404/chezz with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ducklin404/chezz with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("TinyLlama/TinyLlama-1.1B-Chat-v1.0") model = PeftModel.from_pretrained(base_model, "ducklin404/chezz") - Notebooks
- Google Colab
- Kaggle
metadata
base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
datasets:
- ducklin404/chezz_dataset
library_name: peft
tags:
- lora
- qlora
- chess
- tinyllama
- text-generation
- adapter
Model Card for chezz-tinyllama-lora
chezz-tinyllama-lora is a LoRA adapter that adds two skills to TinyLlama-1.1B-Chat-v1.0:
- Select a strong chess move (matching a Stockfish-16 evaluation)
- Explain that move and fire off a light-hearted taunt — all emitted as a single JSON object.
Because only the rank-16 LoRA matrices are shared, the download is tiny (< 100 MB) and license-clean: users still pull the original Apache-2.0 TinyLlama weights.
Model Details
Model Description
| Developed by | Ducklin (aka ducklin404) |
| Financed by | – |
| Shared by | Ducklin |
| Model type | LoRA adapter for a causal language model |
| Languages | English (natural language) + algebraic chess notation |
| License | Apache 2.0 |
| Fine-tuned from | TinyLlama/TinyLlama-1.1B-Chat-v1.0 |
Model Sources
- Code & weights: https://github.com/ducklin404/chezz
- Dataset: https://huggingface.co/datasets/ducklin404/chezz_dataset
- Dev-log / demo: https://asilentpond.com/projects/chezz
Uses
Direct Use
- Drop-in chess-analysis chatbot that replies with:
{"from":"e2","to":"e4","piece":"P","explanation":"…","taunt":"…"}