Text-to-Image
Diffusers
Safetensors
StableDiffusion3Pipeline
sd3
sd3-diffusers
image-to-image
simpletuner
safe-for-work
full
Instructions to use saviski/simpletunner-full-novaskin with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use saviski/simpletunner-full-novaskin with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("saviski/simpletunner-full-novaskin", dtype=torch.bfloat16, device_map="cuda") prompt = "unconditional (blank prompt)" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
| license: other | |
| base_model: "stabilityai/stable-diffusion-3.5-medium" | |
| tags: | |
| - sd3 | |
| - sd3-diffusers | |
| - text-to-image | |
| - image-to-image | |
| - diffusers | |
| - simpletuner | |
| - safe-for-work | |
| - full | |
| pipeline_tag: text-to-image | |
| inference: true | |
| widget: | |
| - text: 'unconditional (blank prompt)' | |
| parameters: | |
| negative_prompt: 'blurry, cropped, ugly' | |
| output: | |
| url: ./assets/image_0_0.png | |
| - text: 'minecraft skin, police officer with dark blue uniform: crisp button‐up shirt tucked into matching pants; sturdy black boots covering lower legs; black tactical gloves on hands; silver badge on left chest; face with focused expression, blue eyes under a peaked cap; short brown hair peeking at nape; utility belt with radio pouches around waist' | |
| parameters: | |
| negative_prompt: 'blurry, cropped, ugly' | |
| output: | |
| url: ./assets/image_1_0.png | |
| - text: 'minecraft skin, fantasy dragon‐scale armor in deep red and gold: overlapping scale plates on chest and shoulders; gauntleted gloves with claw tips on hands; armored greaves on legs; sturdy boots with scale fins; face framed by horned helm opening to reveal green reptilian eyes; dark flowing hair braided into a tail at back' | |
| parameters: | |
| negative_prompt: 'blurry, cropped, ugly' | |
| output: | |
| url: ./assets/image_2_0.png | |
| - text: 'minecraft skin, cyberpunk streetwear: black bio‐leather jacket with neon blue circuit patterns, high‐collar around neck; fingerless gloves on hands; slim cargo pants with glowing seams and knee pads; tech‐bonded boots; face with glowing augmented ocular implants and angular cheek tattoos; buzzed undercut hair in electric purple' | |
| parameters: | |
| negative_prompt: 'blurry, cropped, ugly' | |
| output: | |
| url: ./assets/image_3_0.png | |
| - text: 'minecraft skin, samurai warrior in red and black lacquered armor: layered cuirass over kimono sleeves; wrapped hand‐guards on forearms; hakama trousers tying at calf; straw‐soled sandals on feet; face calm with golden eyes beneath a half‐mask; jet‐black topknot hairstyle' | |
| parameters: | |
| negative_prompt: 'blurry, cropped, ugly' | |
| output: | |
| url: ./assets/image_4_0.png | |
| - text: 'minecraft skin, elven forest scout: green hooded cloak draping over slender shoulders; leather bracers on forearms; fitted tunic and leggings dyed in moss and bark tones; soft boots for silent steps; delicate hands with finger‐woven gloves; face with sharp emerald eyes and freckled cheeks; long auburn hair braided with leaf ornaments' | |
| parameters: | |
| negative_prompt: 'blurry, cropped, ugly' | |
| output: | |
| url: ./assets/image_5_0.png | |
| - text: 'minecraft skin, steampunk mechanic: worn brown leather apron over soot‐stained shirt; fingerless leather gloves with metal knuckle plates on hands; reinforced trousers with tool pockets; heavy leather boots with brass buckles; face smudged with oil, bright hazel eyes behind round goggles; tousled sandy hair' | |
| parameters: | |
| negative_prompt: 'blurry, cropped, ugly' | |
| output: | |
| url: ./assets/image_6_0.png | |
| - text: 'minecraft skin, high‐tech spacesuit: white and blue pressurized suit with panel lines on torso; glove‐sealed sleeves and articulated gauntlets on hands; reinforced leggings with cable conduits to boots; helmet viewport revealing calm face with hazel eyes and chin strap; short dark hair neatly cut' | |
| parameters: | |
| negative_prompt: 'blurry, cropped, ugly' | |
| output: | |
| url: ./assets/image_7_0.png | |
| - text: 'minecraft skin, desert robes: flowing sand‐colored tunic over loose pants; wrapped cloth around forearms and calves; sand‐proof gauntlets on hands; leather sandals on feet; face partially veiled with brown scarf exposing only bright amber eyes; sun‐bleached blonde hair tied back' | |
| parameters: | |
| negative_prompt: 'blurry, cropped, ugly' | |
| output: | |
| url: ./assets/image_8_0.png | |
| - text: 'minecraft skin, shining plate armor: breastplate embossed with crest over padded gambeson; articulated gauntlets on hands; greaves and sabatons covering legs and feet; face visible through open helm, with steely gray eyes and a cropped brown beard; short cropped hair' | |
| parameters: | |
| negative_prompt: 'blurry, cropped, ugly' | |
| output: | |
| url: ./assets/image_9_0.png | |
| - text: 'minecraft skin, arcane mage robes: deep violet robe embroidered with glowing runes on torso and sleeves; delicate fingerless silk gloves on hands; flowing skirt over fitted leggings; soft pointed boots; face with luminous violet eyes and pale skin; long silver hair cascading over shoulders' | |
| parameters: | |
| negative_prompt: 'blurry, cropped, ugly' | |
| output: | |
| url: ./assets/image_10_0.png | |
| # simpletunner-full-novaskin | |
| This is a full rank finetune derived from [stabilityai/stable-diffusion-3.5-medium](https://huggingface.co/stabilityai/stable-diffusion-3.5-medium). | |
| No validation prompt was used during training. | |
| None | |
| ## Validation settings | |
| - CFG: `5.0` | |
| - CFG Rescale: `0.0` | |
| - Steps: `20` | |
| - Sampler: `FlowMatchEulerDiscreteScheduler` | |
| - Seed: `42` | |
| - Resolution: `64x64` | |
| - Skip-layer guidance: | |
| Note: The validation settings are not necessarily the same as the [training settings](#training-settings). | |
| You can find some example images in the following gallery: | |
| <Gallery /> | |
| The text encoder **was not** trained. | |
| You may reuse the base model text encoder for inference. | |
| ## Training settings | |
| - Training epochs: 5 | |
| - Training steps: 60260 | |
| - Learning rate: 1e-06 | |
| - Learning rate schedule: cosine | |
| - Warmup steps: 200 | |
| - Max grad value: 1.0 | |
| - Effective batch size: 12 | |
| - Micro-batch size: 12 | |
| - Gradient accumulation steps: 1 | |
| - Number of GPUs: 1 | |
| - Gradient checkpointing: False | |
| - Prediction type: flow_matching (extra parameters=['shift=3']) | |
| - Optimizer: adamw_bf16 | |
| - Trainable parameter precision: Pure BF16 | |
| - Base model precision: `no_change` | |
| - Caption dropout probability: 0.1% | |
| ## Datasets | |
| ### skins-64 | |
| - Repeats: 0 | |
| - Total number of images: 100000 | |
| - Total number of aspect buckets: 1 | |
| - Resolution: 0.004096 megapixels | |
| - Cropped: False | |
| - Crop style: None | |
| - Crop aspect: None | |
| - Used for regularisation data: No | |
| ### skins-256 | |
| - Repeats: 1 | |
| - Total number of images: 20000 | |
| - Total number of aspect buckets: 1 | |
| - Resolution: 256 px | |
| - Cropped: False | |
| - Crop style: None | |
| - Crop aspect: None | |
| - Used for regularisation data: No | |
| ### skins-heads | |
| - Repeats: 3 | |
| - Total number of images: 5000 | |
| - Total number of aspect buckets: 1 | |
| - Resolution: 256 px | |
| - Cropped: False | |
| - Crop style: None | |
| - Crop aspect: None | |
| - Used for regularisation data: No | |
| ## Inference | |
| ```python | |
| import torch | |
| from diffusers import DiffusionPipeline | |
| model_id = 'saviski/simpletunner-full-novaskin' | |
| pipeline = DiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.bfloat16) # loading directly in bf16 | |
| prompt = "An astronaut is riding a horse through the jungles of Thailand." | |
| negative_prompt = 'blurry, cropped, ugly' | |
| pipeline.to('cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu') # the pipeline is already in its target precision level | |
| model_output = pipeline( | |
| prompt=prompt, | |
| negative_prompt=negative_prompt, | |
| num_inference_steps=20, | |
| generator=torch.Generator(device='cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu').manual_seed(42), | |
| width=64, | |
| height=64, | |
| guidance_scale=5.0, | |
| ).images[0] | |
| model_output.save("output.png", format="PNG") | |
| ``` | |
| ## Exponential Moving Average (EMA) | |
| SimpleTuner generates a safetensors variant of the EMA weights and a pt file. | |
| The safetensors file is intended to be used for inference, and the pt file is for continuing finetuning. | |
| The EMA model may provide a more well-rounded result, but typically will feel undertrained compared to the full model as it is a running decayed average of the model weights. | |