Instructions to use Danrisi/canon_kroma with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Danrisi/canon_kroma with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("lodestones/Kroma", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Danrisi/canon_kroma") prompt = "c2n0n, dslr photo, amateur photo, candid photo, underexposed, high resolution. early-to-mid 2000s digital photograph of a 18 y.o. girl standing beside a cafe entrance during golden hour, waist-up composition, camera positioned several feet in front of her at slightly low chest level, girl occupying the center-right part of the frame, body facing mostly forward while her head turns slightly toward the camera, she is styled as D.Va from Overwatch, real-life casual reinterpretation of D.Va, calm distant expression, looking at the viewer. she is wearing a pink high-neck sweater and an open trench coat, with a subtle D.Va-inspired aesthetic. dark structural column directly behind her, bright open street visible on the right side with pale buildings, utility poles and overhead wires, very strong low evening sun entering from behind and to the right of the girl, face strongly underexposed while the edges of her hair, shoulders and coat glow with bright orange rim light, blown white-yellow highlights in the right background, warm amber sunlight across the whole frame. translucent orange circular flare on the left side, additional soft flare haze around the bright sunlight, strong backlight, deep shadows on her face and clothing, high contrast, crushed blacks, warm orange-brown color cast, background slightly out of focus, distant buildings and street details softly blurred, shallow depth of field, bright background highlights turning into soft glowing bokeh, uneven exposure, slight motion softness, raw amateur dslr photography" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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