Instructions to use AmPac/trace with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use AmPac/trace 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("AmPac/trace") 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 AmPac/trace with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "AmPac/trace" --prompt "Once upon a time"
- Atomic Chat
| { | |
| "fine_tune_type": "lora", | |
| "model": "mlx-community/Qwen2.5-7B-Instruct-4bit", | |
| "lora_parameters": { | |
| "rank": 16, | |
| "dropout": 0.0, | |
| "scale": 20.0 | |
| }, | |
| "num_layers": 16, | |
| "mask_prompt": true, | |
| "max_seq_length": 3072, | |
| "learning_rate": 2e-05, | |
| "iters": 200, | |
| "seed": 0, | |
| "checkpoint": "0000160" | |
| } | |