I build open source AI apps. To finance my work i also build paid versions of my code. But feel free to use the free code. I post features and new projects on https://twitter.com/philz1337x
- 04/12/2024: Multi-step upscaling ()
- 04/07/2024: Resemblance fixed (https://x.com/levelsio/status/1776729356120797265)
- 04/05/2024: Speed Improvements (https://x.com/philz1337x/status/1776121175195975888)
- 04/01/2024: Support custom safetensors checkpoints (https://x.com/philz1337x/status/1774772572632338435)
- 03/28/2024: Anime upscaling (https://x.com/philz1337x/status/1773342568543346738)
- 03/26/2024: LoRa Support (https://x.com/philz1337x/status/1772575319871959180)
- 03/21/2024: Pre downscaling (https://x.com/philz1337x/status/1770680096031961351)
- 03/18/2024: Fractality (https://x.com/philz1337x/status/1769756654533485050)
- 03/15/2024: Code release (https://x.com/philz1337x/status/1768679154726359128)
If you are not fimilar with cog, a1111 and dont't want to use Replicate, you can use my paid version at ClarityAI.cc
If you are not familiar with cog read: cog docs
- Download Checkpoints and LoRa's from Cvitai and put in /models folder (a download_weights.py file to prepare everything with one file is a work in progress)
https://civitai.com/models/46422/juggernaut
https://civitai.com/models/82098?modelVersionId=87153
https://civitai.com/models/171159?modelVersionId=236130
- predict with cog:
cog predict -i image="link-to-image"
https://github.com/AUTOMATIC1111/stable-diffusion-webui
- Use these params:
masterpiece, best quality, highres, <lora:more_details:0.5> <lora:SDXLrender_v2.0:1> Negative prompt: (worst quality, low quality, normal quality:2) JuggernautNegative-neg Steps: 18, Sampler: DPM++ 3M SDE Karras, CFG scale: 6.0, Seed: 1337, Size: 1024x1024, Model hash: 338b85bc4f, Model: juggernaut_reborn, Denoising strength: 0.35, Tiled Diffusion upscaler: 4x-UltraSharp, Tiled Diffusion scale factor: 2, Tiled Diffusion: {"Method": "MultiDiffusion", "Tile tile width": 112, "Tile tile height": 144, "Tile Overlap": 4, "Tile batch size": 8, "Upscaler": "4x-UltraSharp", "Upscale factor": 2, "Keep input size": true}, ControlNet 0: "Module: tile_resample, Model: control_v11f1e_sd15_tile, Weight: 0.6, Resize Mode: 1, Low Vram: False, Processor Res: 512, Threshold A: 1, Threshold B: 1, Guidance Start: 0.0, Guidance End: 1.0, Pixel Perfect: True, Control Mode: 1, Hr Option: HiResFixOption.BOTH, Save Detected Map: False", Lora hashes: "more_details: 3b8aa1d351ef, SDXLrender_v2.0: 3925cf4759af"