Image-Text-to-Text
MLX
Safetensors
unlimited-ocr
ax-engine
mlx-vlm
ocr
mxfp8
int8
apple-silicon
automatosx
conversational
8-bit precision
Instructions to use AutomatosX/AX-Unlimited-OCR-3B-MoE-MLX-MXFP8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use AutomatosX/AX-Unlimited-OCR-3B-MoE-MLX-MXFP8 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("AutomatosX/AX-Unlimited-OCR-3B-MoE-MLX-MXFP8") config = load_config("AutomatosX/AX-Unlimited-OCR-3B-MoE-MLX-MXFP8") # 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
| { | |
| "model_path": "sahilchachra/unlimited-ocr-mxfp8-mlx", | |
| "served_revision": "55b8031a6c867de675279d9604e38cc94b9882a4", | |
| "image_path": "test_invoice.png", | |
| "prompt": "<image>document parsing.", | |
| "max_tokens": 256, | |
| "system": { | |
| "platform": "macOS-26.5.2-arm64-arm-64bit-Mach-O", | |
| "processor": "arm", | |
| "python_version": "3.14.6", | |
| "machine": "arm64", | |
| "mlx_version": "0.32.0", | |
| "mlx_vlm_version": "0.6.6", | |
| "chip": "Apple M3 Max", | |
| "total_memory_gb": 128.0 | |
| }, | |
| "model_load_time_seconds": 2.9305669579916866, | |
| "memory_after_load_mb": 3992.859375, | |
| "num_warmup": 1, | |
| "num_runs": 3, | |
| "mean_tps": 35.07146198590831, | |
| "std_tps": 0.290807343078657, | |
| "mean_elapsed_seconds": 8.953089208662277, | |
| "mean_peak_memory_mb": 5165.991419999999, | |
| "runs": [ | |
| { | |
| "run": 1, | |
| "elapsed_seconds": 9.042429541994352, | |
| "tokens_generated": 256, | |
| "tokens_generated_source": "mlx-vlm token count", | |
| "tokens_per_second": 34.74497597308309, | |
| "tokens_per_second_source": "mlx-vlm generation_tps", | |
| "peak_memory_mb": 5165.81578, | |
| "memory_delta_mb": 1337.186768, | |
| "process_peak_rss_mb": 4022.6875, | |
| "prompt_tokens": 697, | |
| "prompt_tokens_per_second": 429.97806661114964, | |
| "finish_reason": "length" | |
| }, | |
| { | |
| "run": 2, | |
| "elapsed_seconds": 9.023512416999438, | |
| "tokens_generated": 256, | |
| "tokens_generated_source": "mlx-vlm token count", | |
| "tokens_per_second": 35.01812122387363, | |
| "tokens_per_second_source": "mlx-vlm generation_tps", | |
| "peak_memory_mb": 5166.07924, | |
| "memory_delta_mb": 1337.188084, | |
| "process_peak_rss_mb": 4023.046875, | |
| "prompt_tokens": 697, | |
| "prompt_tokens_per_second": 417.40764558358615, | |
| "finish_reason": "length" | |
| }, | |
| { | |
| "run": 3, | |
| "elapsed_seconds": 8.793325666993042, | |
| "tokens_generated": 256, | |
| "tokens_generated_source": "mlx-vlm token count", | |
| "tokens_per_second": 35.451288760768186, | |
| "tokens_per_second_source": "mlx-vlm generation_tps", | |
| "peak_memory_mb": 5166.07924, | |
| "memory_delta_mb": 1337.188084, | |
| "process_peak_rss_mb": 4023.3125, | |
| "prompt_tokens": 697, | |
| "prompt_tokens_per_second": 449.69288066410945, | |
| "finish_reason": "length" | |
| } | |
| ] | |
| } |