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
File size: 317 Bytes
d5efc46 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | {
"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"
}
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