Text-to-Image
MLX
MiniMax H3
Safetensors
English
apple-silicon
macos
image-to-image
image-editing
image-generation
Instructions to use devin-lai/MiniMax-H3-Image-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use devin-lai/MiniMax-H3-Image-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download devin-lai/MiniMax-H3-Image-mlx --local-dir MiniMax-H3-Image-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
File size: 2,155 Bytes
3da88e3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 | {
"prompt": "An intimate natural-light portrait of an elderly woman in a botanical conservatory, reading a small red clothbound book. Warm brown skin with visible freckles and fine wrinkles, silver curls lit from behind, intricate indigo knit cardigan. Soft fern fronds out of focus in the foreground; detailed hands and realistic skin texture. A candid 85mm color photograph with gentle shadows and no lettering.",
"seed": 1234,
"size": [
2048,
2048
],
"canvas": [
2048,
2048
],
"rng": "torch",
"reference_images": [],
"reference_sha256": [],
"sigmas": [
1.0,
0.9675236940383911,
0.8875485062599182,
0.75,
0.5327739119529724,
0.23200887441635132,
0.0
],
"steps": [
0,
1,
2,
3,
4,
5
],
"vae": {
"tile_batch": 8,
"package": "cache/coreml-v2/vae-batch8.mlpackage",
"compute_units": "CPU_AND_GPU"
},
"vae_backend": "coreml",
"environment": {
"platform": "macOS-27.0.1-arm64-arm-64bit",
"machine": "arm64",
"metal": {
"device_name": "Apple M5 Pro",
"max_recommended_working_set_size": 55662788608,
"memory_size": 68719476736,
"architecture": "applegpu_g17s",
"max_buffer_length": 41747087360,
"resource_limit": 499000
},
"versions": {
"mlx": "0.32.4",
"mlx-metal": "0.32.4",
"numpy": "2.5.4",
"safetensors": "0.8.0",
"transformers": "4.57.6",
"torch": "2.15.0",
"Pillow": "13.0.0",
"scikit-image": "0.26.0"
},
"precision_environment": {
"MLX_ENABLE_TF32": "0",
"MLX_CONV_WINOGRAD": "0"
}
},
"validation_scope": "Same final latent; decoder only",
"timing_scope": "Warm decoder only; model loading excluded",
"timings": {
"decode_s": 1.591182250645943
},
"source_trace": "outputs/optimization-v2/portrait/wired-baseline-2.trace.safetensors",
"source_trace_sha256": "5808ccec8c5049ce2761d0b5f41638e28107b287c9e63fe6bef175e600c9c6c8",
"output": "comparisons/optimization-v2/decoder-portrait/coreml-CPU_AND_GPU.png",
"png_sha256": "ad830fa42d204982381787317eee53f4c662d512cbafe260a53e065b987c18c6"
}
|