Instructions to use MarkBW/cinematic-shot-xl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MarkBW/cinematic-shot-xl with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("xinsir/controlnet-union-sdxl-1.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("MarkBW/cinematic-shot-xl") prompt = "UNICODE\u0000\u0000c\u0000i\u0000n\u0000e\u0000m\u0000a\u0000t\u0000i\u0000c\u0000,\u0000 \u0000w\u0000o\u0000m\u0000a\u0000n\u0000 \u0000e\u0000y\u0000e\u0000s\u0000,\u0000 \u0000g\u0000a\u0000z\u0000e\u0000,\u0000 \u0000c\u0000l\u0000o\u0000s\u0000e\u0000-\u0000u\u0000p\u0000,\u0000 \u0000d\u0000a\u0000r\u0000k\u0000,\u0000 \u0000f\u0000i\u0000l\u0000m\u0000 \u0000g\u0000r\u0000a\u0000i\u0000n\u0000,\u0000 \u0000m\u0000e\u0000d\u0000i\u0000e\u0000v\u0000a\u0000l\u0000 \u0000d\u0000u\u0000n\u0000g\u0000e\u0000o\u0000n\u0000,\u0000 \u0000t\u0000o\u0000c\u0000h\u0000,\u0000 \u0000m\u0000e\u0000d\u0000i\u0000e\u0000v\u0000a\u0000l\u0000 \u0000f\u0000a\u0000n\u0000t\u0000a\u0000s\u0000y\u0000,\u0000 \u0000s\u0000i\u0000d\u0000e\u0000 \u0000v\u0000i\u0000e\u0000w\u0000 \u0001�\u0000/\u00002\u00002\u0000,\u0000 \u0000U\u0000r\u0000b\u0000a\u0000n\u0000,\u0000 \u0000S\u0000h\u0000o\u0000r\u0000t\u0000 \u0000t\u0000e\u0000l\u0000e\u0000p\u0000h\u0000o\u0000t\u0000o\u0000 \u0000f\u0000o\u0000c\u0000a\u0000l\u0000 \u0000l\u0000e\u0000n\u0000g\u0000t\u0000h\u0000,\u0000 \u0000s\u0000h\u0000o\u0000t\u0000 \u0000o\u0000n\u0000 \u0000A\u0000L\u0000E\u0000X\u0000A\u0000 \u00006\u00005\u0000,\u0000 \u0000d\u0000a\u0000r\u0000k\u0000,\u0000 \u0000l\u0000i\u0000g\u0000h\u0000t\u0000 \u0000o\u0000n\u0000 \u0000f\u0000a\u0000c\u0000e\u0000,\u0000 \u0000<\u0000l\u0000o\u0000r\u0000a\u0000:\u0000C\u0000i\u0000n\u0000e\u0000m\u0000a\u0000t\u0000i\u0000c\u0000S\u0000t\u0000y\u0000l\u0000e\u0000_\u0000v\u00001\u0000:\u0000.\u00008\u0000>\u0000" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("xinsir/controlnet-union-sdxl-1.0", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("MarkBW/cinematic-shot-xl")
prompt = "UNICODE\u0000\u0000c\u0000i\u0000n\u0000e\u0000m\u0000a\u0000t\u0000i\u0000c\u0000,\u0000 \u0000w\u0000o\u0000m\u0000a\u0000n\u0000 \u0000e\u0000y\u0000e\u0000s\u0000,\u0000 \u0000g\u0000a\u0000z\u0000e\u0000,\u0000 \u0000c\u0000l\u0000o\u0000s\u0000e\u0000-\u0000u\u0000p\u0000,\u0000 \u0000d\u0000a\u0000r\u0000k\u0000,\u0000 \u0000f\u0000i\u0000l\u0000m\u0000 \u0000g\u0000r\u0000a\u0000i\u0000n\u0000,\u0000 \u0000m\u0000e\u0000d\u0000i\u0000e\u0000v\u0000a\u0000l\u0000 \u0000d\u0000u\u0000n\u0000g\u0000e\u0000o\u0000n\u0000,\u0000 \u0000t\u0000o\u0000c\u0000h\u0000,\u0000 \u0000m\u0000e\u0000d\u0000i\u0000e\u0000v\u0000a\u0000l\u0000 \u0000f\u0000a\u0000n\u0000t\u0000a\u0000s\u0000y\u0000,\u0000 \u0000s\u0000i\u0000d\u0000e\u0000 \u0000v\u0000i\u0000e\u0000w\u0000 \u0001�\u0000/\u00002\u00002\u0000,\u0000 \u0000U\u0000r\u0000b\u0000a\u0000n\u0000,\u0000 \u0000S\u0000h\u0000o\u0000r\u0000t\u0000 \u0000t\u0000e\u0000l\u0000e\u0000p\u0000h\u0000o\u0000t\u0000o\u0000 \u0000f\u0000o\u0000c\u0000a\u0000l\u0000 \u0000l\u0000e\u0000n\u0000g\u0000t\u0000h\u0000,\u0000 \u0000s\u0000h\u0000o\u0000t\u0000 \u0000o\u0000n\u0000 \u0000A\u0000L\u0000E\u0000X\u0000A\u0000 \u00006\u00005\u0000,\u0000 \u0000d\u0000a\u0000r\u0000k\u0000,\u0000 \u0000l\u0000i\u0000g\u0000h\u0000t\u0000 \u0000o\u0000n\u0000 \u0000f\u0000a\u0000c\u0000e\u0000,\u0000 \u0000<\u0000l\u0000o\u0000r\u0000a\u0000:\u0000C\u0000i\u0000n\u0000e\u0000m\u0000a\u0000t\u0000i\u0000c\u0000S\u0000t\u0000y\u0000l\u0000e\u0000_\u0000v\u00001\u0000:\u0000.\u00008\u0000>\u0000"
image = pipe(prompt).images[0]cinematic-shot-xl

- Prompt
- UNICODEcinematic, woman eyes, gaze, close-up, dark, film grain, medieval dungeon, toch, medieval fantasy, side view �/22, Urban, Short telephoto focal length, shot on ALEXA 65, dark, light on face, <lora:CinematicStyle_v1:.8>
Model description
Cinematic color grading style from movies
By: ZyloO
Trigger words
You should use cinematic to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
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