Instructions to use sruly/human-chess-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use sruly/human-chess-mlx with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # if on a CUDA device, also pip install mlx[cuda] # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("sruly/human-chess-mlx") prompt = "Once upon a time in" text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use sruly/human-chess-mlx with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "sruly/human-chess-mlx" --prompt "Once upon a time"
- Atomic Chat
| { | |
| "legal_masked_top1_accuracy": 0.30970463160285916, | |
| "legal_masked_top5_accuracy": 0.6682182988643823, | |
| "raw_top1_accuracy": 0.27678346260393144, | |
| "raw_top1_legal_rate": 0.8729143926399501, | |
| "test_legal_masked_top1_accuracy": 0.307254982970034, | |
| "test_legal_masked_top5_accuracy": 0.6651906703856502, | |
| "test_move_bits": 4.1147322227098035, | |
| "test_raw_top1_accuracy": 0.27385924925821303, | |
| "test_raw_top1_legal_rate": 0.8720350759973353, | |
| "val_move_bits": 4.098970468943424 | |
| } | |