Instructions to use SceneWorks/sd3.5-medium-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SceneWorks/sd3.5-medium-mlx with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SceneWorks/sd3.5-medium-mlx", torch_dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - MLX
How to use SceneWorks/sd3.5-medium-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir sd3.5-medium-mlx SceneWorks/sd3.5-medium-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Draw Things
- DiffusionBee
| license: other | |
| license_name: stabilityai-ai-community | |
| license_link: LICENSE.md | |
| base_model: stabilityai/stable-diffusion-3.5-medium | |
| pipeline_tag: text-to-image | |
| tags: | |
| - text-to-image | |
| - stable-diffusion | |
| - stable-diffusion-3 | |
| - mlx | |
| - sceneworks | |
| # Stable Diffusion 3.5 Medium — SceneWorks MLX quant matrix | |
| Pre-built, turnkey MLX tiers of **Stability AI Stable Diffusion 3.5 Medium** — the 2.5B MMDiT-X (dual-attention) mid-tier, renders up to 1440² for | |
| [SceneWorks](https://github.com/SceneWorks/SceneWorks), hosted as separate downloadable artifacts so | |
| the app loads a tier directly with **no on-device conversion peak** (sc-8513, epic 8506). | |
| Each subdirectory is a complete `from_snapshot`-loadable diffusers tree — packed/dense | |
| `transformer/` plus the dense triple text encoder (CLIP-L + CLIP-G + T5-XXL), tokenizers, and 16-ch | |
| VAE: | |
| | Tier | `transformer/` precision | Use | | |
| | --- | --- | --- | | |
| | `q4/` | Q4 (asymmetric group-affine, group-64) — **default** | lowest memory | | |
| | `q8/` | Q8 (asymmetric group-affine, group-64) | near-lossless | | |
| | `bf16/`| dense bf16 (the source backbone, no quantization) | highest fidelity, high-memory Macs | | |
| Only the MMDiT transformer is quantized; the text encoders and VAE are reused dense in every tier. | |
| The packed weights auto-detect their quantization on load. | |
| ## License & attribution | |
| This model is a derivative of **Stable Diffusion 3.5 Large** and is distributed under the | |
| **[Stability AI Community License](LICENSE.md)** (free for research, non-commercial, and commercial | |
| use by organizations with under \$1M in annual revenue; see the license for terms). | |
| > This Stability AI Model is licensed under the Stability AI Community License, Copyright © Stability | |
| > AI Ltd. All Rights Reserved. | |
| **Powered by Stability AI.** | |