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: 305 Bytes
8932cec | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | {
"architectures": [
"GPT"
],
"library_name": "mlx",
"model_config": {
"n_embd": 384,
"n_head": 3,
"n_kv_head": 3,
"n_layer": 6,
"sequence_len": 256,
"vocab_size": 2075,
"window_pattern": "SSSL"
},
"model_type": "human-chess-mlx",
"torch_dtype": "bfloat16"
}
|