Instructions to use salakash/Minimalism with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use salakash/Minimalism 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("salakash/Minimalism") prompt = "Once upon a time in" text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
- MLX LM
How to use salakash/Minimalism with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "salakash/Minimalism" --prompt "Once upon a time"
| { | |
| "model_id": "mlx-community/Qwen2.5-Coder-0.5B-Instruct-4bit", | |
| "dataset_id": "flwrlabs/code-alpaca-20k", | |
| "iters": 100, | |
| "rank": 8, | |
| "alpha": 16, | |
| "dropout": 0.05, | |
| "learning_rate": 2e-05, | |
| "timestamp": "2025-12-31T15:18:04.451022Z" | |
| } |