tags:
- text-to-image
- stable-diffusion
- lora
- diffusers
- image-generation
- flux
- safetensors
widget:
- text: >-
This poster shows a smartphone on a black background. The iphone screen
shows a miniature scene, an amusement park scene, seamlessly integrated
into the phone's frame. The scene is set from the top left to the bottom
right of the phone, creating a perspective that draws the viewer into the
tiny world. In the middle is a huge Ferris wheel, surrounded by many
amusement facilities and shops
output:
url: images/577fa923f011853d6e96afd3dbd05810cf85625fec0614a36ca5e490.jpg
- text: >-
This poster shows a smartphone on a black background. The iphone screen
shows a miniature scene, a street scene, seamlessly integrated into the
iphone's frame. The scene is set from the top left to the bottom right of
the phone, creating a perspective that draws the viewer into the tiny
world. In the middle of the picture is the apple Store, which is a glass
house. It is surrounded by shopping malls and shops
output:
url: images/a29b8763a8f733dea09c1ab07a42263ef6e304cb81be3f5c97fbf8f6.jpg
- text: >-
This poster shows a smartphone against a dark background. The phone screen
reveals a miniature stereoscopic scene of eiffel tower, Paris, seamlessly
integrated into the phone’s frame
output:
url: images/c4f5c765bc8d3d396ed13d65666895ab23ada35c78ca6d91bf814613.jpg
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: null
license: other
license_name: flux-1-dev-non-commercial-license
license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md
FLUX.1-dev-LoRA-Micro-landscape-on-Mobile-Phone
This is a LoRA trained on FLUX.1-dev for micro landscape on mobile phone by DalaBengba on Shakker AI.
Showcases
- Prompt
- This poster shows a smartphone on a black background. The iphone screen shows a miniature scene, an amusement park scene, seamlessly integrated into the phone's frame. The scene is set from the top left to the bottom right of the phone, creating a perspective that draws the viewer into the tiny world. In the middle is a huge Ferris wheel, surrounded by many amusement facilities and shops
- Prompt
- This poster shows a smartphone on a black background. The iphone screen shows a miniature scene, a street scene, seamlessly integrated into the iphone's frame. The scene is set from the top left to the bottom right of the phone, creating a perspective that draws the viewer into the tiny world. In the middle of the picture is the apple Store, which is a glass house. It is surrounded by shopping malls and shops
- Prompt
- This poster shows a smartphone against a dark background. The phone screen reveals a miniature stereoscopic scene of eiffel tower, Paris, seamlessly integrated into the phone’s frame
Trigger words
The trigger word is not required. The recommended scale is 0.6 to 0.9 in diffusers.
Usage suggestion
When you come up with a scene, you can directly give it to GPT to enrich the details. At the beginning, you can tell it this: 'I am using AI drawing software for creation, and I need you to help me write some prompts in natural language. Start the sentence like this: This poster shows a smartphone against a dark background. The phone screen reveals a miniature scene of a xxxxxxx landscape, seamlessly integrated into the phone’s frame. In this sentence, xxxxxxx represents the specific scene. After this sentence, add some specific details about the scene.
Inference
import torch
from diffusers import FluxPipeline
pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16)
pipe.load_lora_weights("Shakker-Labs/FLUX.1-dev-LoRA-Micro-landscape-on-Mobile-Phone", weight_name="FLUX-dev-lora-micro-landscape.safetensors")
pipe.fuse_lora(lora_scale=0.7)
pipe.to("cuda")
prompt = "This poster shows a smartphone against a dark background. The phone screen reveals a miniature stereoscopic scene of New York City, seamlessly integrated into the phone’s frame."
image = pipe(prompt,
num_inference_steps=24,
guidance_scale=3.5,
).images[0]
image.save(f"example.png")
Online Inference
You can also run this model at Shakker AI, where we provide an online interface to generate images.
Acknowledgements
This model is trained by our copyrighted users DalaBengba. We release this model under permissions. The model follows flux-1-dev-non-commercial-license.