Text-to-Image
Diffusers
Safetensors
GGUF
Flux2KleinPipeline
flux
photography
realism
image-generation
Instructions to use kitaniai/morgana-1.2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kitaniai/morgana-1.2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kitaniai/morgana-1.2", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("kitaniai/morgana-1.2", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]Kitani Morgana v1.2
The photography model that doesn't look like it came from a model.
Morgana v1.2 is Kitani's image model, built in partnership with ShuttleAI and trained in part on the Shuttle 3 Jaguar dataset. It's tuned for one thing above all: images you'd believe were shot on a camera. Golden-hour landscapes, candid phone selfies, macro textures, moody night streets and painted art, all with natural light, honest color and real-world detail.
What it does best
- Realistic photography - soft window light, deep shadows, film-like grain and subtle lens character instead of plastic HDR renders
- Human faces that feel human - front-camera selfies, candid moments, visible pores, flyaway hair and imperfect framing
- Macro and material detail - water droplets, feather barbs, fabric weave, wood grain, rusted metal, worn leather
- Cinematic landscapes - aurora mirrored in alpine lakes, waves breaking on black sand, mist in the pines
- Atmospheric nights - neon glowing on wet asphalt, believable low-light exposure
- Art styles on demand - thick impasto oil paintings, luminous watercolor, film-still anime and hyperreal 3D renders
Quick start
import torch
from diffusers import Flux2KleinPipeline
pipe = Flux2KleinPipeline.from_pretrained(
"kitani/morgana-v1.2",
torch_dtype=torch.bfloat16,
).to("cuda")
image = pipe(
prompt="A realistic macro photograph of a water droplet on a waxy green leaf, fine veins, soft daylight, shallow depth of field.",
width=1024,
height=1024,
num_inference_steps=28,
guidance_scale=4.0,
max_sequence_length=512,
generator=torch.Generator("cuda").manual_seed(12345),
).images[0]
How to write prompts Morgana loves
Describe the shot like a photographer would:
- Lighting - "soft window light", "golden hour", "overcast sky", "neon reflections"
- Lens and framing - "85mm", "shallow depth of field", "wide-angle", "off-center"
- Texture and reality - "visible pores", "natural skin texture", "film grain", "subtle imperfections"
- Keep it clean - end prompts with "no text" when you don't want signage
Notes
- Negative prompts are not supported by this pipeline.
- Readable text and signage are not Morgana's strength โ ask for clean scenes when it matters.
- The right prompt turns good into great; the examples above are a strong starting point.
Credits
Built by Kitani in partnership with ShuttleAI, using the Shuttle 3 Jaguar dataset.
License
Licensed by Kitani, Inc. (https://kitani.ai). See the base model card for underlying model terms.
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Model tree for kitaniai/morgana-1.2
Base model
black-forest-labs/FLUX.2-klein-base-4B