Instructions to use mlx-community/gemma-4-26b-a4b-bf16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/gemma-4-26b-a4b-bf16 with MLX:
# Make sure mlx-vlm is installed # pip install --upgrade mlx-vlm from mlx_vlm import load, generate from mlx_vlm.prompt_utils import apply_chat_template from mlx_vlm.utils import load_config # Load the model model, processor = load("mlx-community/gemma-4-26b-a4b-bf16") config = load_config("mlx-community/gemma-4-26b-a4b-bf16") # Prepare input image = ["http://images.cocodataset.org/val2017/000000039769.jpg"] prompt = "Describe this image." # Apply chat template formatted_prompt = apply_chat_template( processor, config, prompt, num_images=1 ) # Generate output output = generate(model, processor, formatted_prompt, image) print(output) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Download generation_config.json from mlx-community/gemma-4-26b-a4b-bf16: direct link, hf CLI and curl.
- Browser
- Download file 181 Bytes
-
https://huggingface.co/mlx-community/gemma-4-26b-a4b-bf16/resolve/main/generation_config.json
- Command line
-
hf download hf://mlx-community/gemma-4-26b-a4b-bf16/generation_config.json
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curl -L -o generation_config.json https://huggingface.co/mlx-community/gemma-4-26b-a4b-bf16/resolve/main/generation_config.json
181 Bytes
| { | |
| "bos_token_id": 2, | |
| "do_sample": true, | |
| "eos_token_id": 1, | |
| "pad_token_id": 0, | |
| "temperature": 1.0, | |
| "top_k": 64, | |
| "top_p": 0.95, | |
| "transformers_version": "5.5.0.dev0" | |
| } | |