Instructions to use Youssofal/Gemma4-MTPLX-Optimized-Speed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use Youssofal/Gemma4-MTPLX-Optimized-Speed 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("Youssofal/Gemma4-MTPLX-Optimized-Speed") 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 Youssofal/Gemma4-MTPLX-Optimized-Speed with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "Youssofal/Gemma4-MTPLX-Optimized-Speed" --prompt "Once upon a time"
File size: 307 Bytes
cc1cd06 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | {
"bos_token_id": 2,
"do_sample": true,
"eos_token_id": [
1,
106,
50
],
"is_assistant": true,
"num_assistant_tokens": 6,
"num_assistant_tokens_schedule": "constant",
"pad_token_id": 0,
"temperature": 1.0,
"top_k": 64,
"top_p": 0.95,
"transformers_version": "5.7.0.dev0"
} |