Instructions to use kernkraft/F2K9_UltimateUpscaler with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kernkraft/F2K9_UltimateUpscaler with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("kernkraft/F2K9_UltimateUpscaler") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
YAML Metadata Error:"base_model" is not allowed to be empty
Ultimate Upscaler

- Prompt
- -

- Prompt
- -

- Prompt
- -
Model description
Re-upload so I can use it on fal.ai for personal use Original
Trigger: restore the image quality, remove any compression artefacts, remove any haze and soft edges, enrich the original with new intricate detail in all textures and surfaces createing a professional photorealistic photograph with natral lighting and skin texture,
Trigger words
You should use restore the image quality to trigger the image generation.
You should use remove any compression artefacts to trigger the image generation.
You should use remove any haze and soft edges to trigger the image generation.
You should use enrich the original with new intricate detail in all textures and surfaces createing a professional photorealistic photograph with natral lighting and skin texture to trigger the image generation.
Download model
Download them in the Files & versions tab.
- Downloads last month
- 33