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
File size: 487 Bytes
8932cec | 1 2 3 4 5 6 7 8 9 10 11 12 13 | {
"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
}
|