deepfates/flux-utopian-scholastic 🖼️🔢❓📝✓ → 🖼️
About
A FLUX model fine-tuned on images of the Utopian Scholastic aesthetic. Good at text too
Example Output
"UTPN style image of "Utopian Scholastic" title card, space, blonde-haired woman, VR goggles, virtual reality, cosmic technology, gloved hand. This artwork features a futuristic rendering of a woman wearing sleek, silver, cybernetic VR goggles, her long blonde hair flowing in a sci-fi environment. The focus is on her eyes, framed by the VR glasses, with a mirrored string of pearls excluding her gaze. A white gloved hand reaches out in front of her against a backdrop of swirling white light and stars. Abstract elements blend with technological symbols, creating a dynamic scene, contrasting retro aesthetics with bold, modern lines. The text reads "Utopian Scholastic" in UTPN font"
Output
Performance Metrics
All Input Parameters
{
"model": "dev",
"prompt": "UTPN style image of \"Utopian Scholastic\" title card, space, blonde-haired woman, VR goggles, virtual reality, cosmic technology, gloved hand. This artwork features a futuristic rendering of a woman wearing sleek, silver, cybernetic VR goggles, her long blonde hair flowing in a sci-fi environment. The focus is on her eyes, framed by the VR glasses, with a mirrored string of pearls excluding her gaze. A white gloved hand reaches out in front of her against a backdrop of swirling white light and stars. Abstract elements blend with technological symbols, creating a dynamic scene, contrasting retro aesthetics with bold, modern lines. The text reads \"Utopian Scholastic\" in UTPN font",
"go_fast": false,
"lora_scale": 1.3,
"megapixels": "1",
"num_outputs": 1,
"aspect_ratio": "4:5",
"output_format": "webp",
"guidance_scale": 3,
"output_quality": 80,
"prompt_strength": 0.8,
"extra_lora_scale": 1,
"num_inference_steps": 31
}
Input Parameters
- mask
- Image mask for image inpainting mode. If provided, aspect_ratio, width, and height inputs are ignored.
- seed
- Random seed. Set for reproducible generation
- image
- Input image for image to image or inpainting mode. If provided, aspect_ratio, width, and height inputs are ignored.
- model
- Which model to run inference with. The dev model performs best with around 28 inference steps but the schnell model only needs 4 steps.
- width
- Width of generated image. Only works if `aspect_ratio` is set to custom. Will be rounded to nearest multiple of 16. Incompatible with fast generation
- height
- Height of generated image. Only works if `aspect_ratio` is set to custom. Will be rounded to nearest multiple of 16. Incompatible with fast generation
- prompt (required)
- Prompt for generated image. If you include the `trigger_word` used in the training process you are more likely to activate the trained object, style, or concept in the resulting image.
- go_fast
- Run faster predictions with model optimized for speed (currently fp8 quantized); disable to run in original bf16
- extra_lora
- Load LoRA weights. Supports Replicate models in the format <owner>/<username> or <owner>/<username>/<version>, HuggingFace URLs in the format huggingface.co/<owner>/<model-name>, CivitAI URLs in the format civitai.com/models/<id>[/<model-name>], or arbitrary .safetensors URLs from the Internet. For example, 'fofr/flux-pixar-cars'
- lora_scale
- Determines how strongly the main LoRA should be applied. Sane results between 0 and 1 for base inference. For go_fast we apply a 1.5x multiplier to this value; we've generally seen good performance when scaling the base value by that amount. You may still need to experiment to find the best value for your particular lora.
- megapixels
- Approximate number of megapixels for generated image
- num_outputs
- Number of outputs to generate
- aspect_ratio
- Aspect ratio for the generated image. If custom is selected, uses height and width below & will run in bf16 mode
- output_format
- Format of the output images
- guidance_scale
- Guidance scale for the diffusion process. Lower values can give more realistic images. Good values to try are 2, 2.5, 3 and 3.5
- output_quality
- Quality when saving the output images, from 0 to 100. 100 is best quality, 0 is lowest quality. Not relevant for .png outputs
- prompt_strength
- Prompt strength when using img2img. 1.0 corresponds to full destruction of information in image
- extra_lora_scale
- Determines how strongly the extra LoRA should be applied. Sane results between 0 and 1 for base inference. For go_fast we apply a 1.5x multiplier to this value; we've generally seen good performance when scaling the base value by that amount. You may still need to experiment to find the best value for your particular lora.
- replicate_weights
- Load LoRA weights. Supports Replicate models in the format <owner>/<username> or <owner>/<username>/<version>, HuggingFace URLs in the format huggingface.co/<owner>/<model-name>, CivitAI URLs in the format civitai.com/models/<id>[/<model-name>], or arbitrary .safetensors URLs from the Internet. For example, 'fofr/flux-pixar-cars'
- num_inference_steps
- Number of denoising steps. More steps can give more detailed images, but take longer.
- disable_safety_checker
- Disable safety checker for generated images.
Output Schema
Output
Example Execution Logs
Weights already loaded Loaded LoRAs in 0.03s Using seed: 64593 Prompt: UTPN style image of "Utopian Scholastic" title card, space, blonde-haired woman, VR goggles, virtual reality, cosmic technology, gloved hand. This artwork features a futuristic rendering of a woman wearing sleek, silver, cybernetic VR goggles, her long blonde hair flowing in a sci-fi environment. The focus is on her eyes, framed by the VR glasses, with a mirrored string of pearls excluding her gaze. A white gloved hand reaches out in front of her against a backdrop of swirling white light and stars. Abstract elements blend with technological symbols, creating a dynamic scene, contrasting retro aesthetics with bold, modern lines. The text reads "Utopian Scholastic" in UTPN font [!] txt2img mode 0%| | 0/31 [00:00<?, ?it/s] 3%|▎ | 1/31 [00:00<00:07, 3.92it/s] 6%|▋ | 2/31 [00:00<00:06, 4.34it/s] 10%|▉ | 3/31 [00:00<00:06, 4.20it/s] 13%|█▎ | 4/31 [00:00<00:06, 4.13it/s] 16%|█▌ | 5/31 [00:01<00:06, 4.10it/s] 19%|█▉ | 6/31 [00:01<00:06, 4.08it/s] 23%|██▎ | 7/31 [00:01<00:05, 4.06it/s] 26%|██▌ | 8/31 [00:01<00:05, 4.06it/s] 29%|██▉ | 9/31 [00:02<00:05, 4.05it/s] 32%|███▏ | 10/31 [00:02<00:05, 4.05it/s] 35%|███▌ | 11/31 [00:02<00:04, 4.05it/s] 39%|███▊ | 12/31 [00:02<00:04, 4.05it/s] 42%|████▏ | 13/31 [00:03<00:04, 4.06it/s] 45%|████▌ | 14/31 [00:03<00:04, 4.05it/s] 48%|████▊ | 15/31 [00:03<00:03, 4.05it/s] 52%|█████▏ | 16/31 [00:03<00:03, 4.06it/s] 55%|█████▍ | 17/31 [00:04<00:03, 4.06it/s] 58%|█████▊ | 18/31 [00:04<00:03, 4.05it/s] 61%|██████▏ | 19/31 [00:04<00:02, 4.05it/s] 65%|██████▍ | 20/31 [00:04<00:02, 4.06it/s] 68%|██████▊ | 21/31 [00:05<00:02, 4.06it/s] 71%|███████ | 22/31 [00:05<00:02, 4.05it/s] 74%|███████▍ | 23/31 [00:05<00:01, 4.06it/s] 77%|███████▋ | 24/31 [00:05<00:01, 4.06it/s] 81%|████████ | 25/31 [00:06<00:01, 4.07it/s] 84%|████████▍ | 26/31 [00:06<00:01, 4.06it/s] 87%|████████▋ | 27/31 [00:06<00:00, 4.06it/s] 90%|█████████ | 28/31 [00:06<00:00, 4.07it/s] 94%|█████████▎| 29/31 [00:07<00:00, 4.06it/s] 97%|█████████▋| 30/31 [00:07<00:00, 4.04it/s] 100%|██████████| 31/31 [00:07<00:00, 4.06it/s] 100%|██████████| 31/31 [00:07<00:00, 4.07it/s] Total safe images: 1 out of 1
Version Details
- Version ID
6d07450fbdd415a5b2d4bf4aca4eb9a9c34cd77812483869406a7bb2c33d022a- Version Created
- May 1, 2025