Instructions to use SpiderSteeped/shrink with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SpiderSteeped/shrink with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("SpiderSteeped/shrink") prompt = "Late 2010s smartphone photo, naturally lit with morning light spilling in from an unseen kitchen window, captured in shallow focus with warm white balance and slight digital grain." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from SpiderSteeped/shrink: direct link, hf CLI and curl.
- Browser
- Download file 692 Bytes
-
https://huggingface.co/SpiderSteeped/shrink/resolve/main/README.md
- Command line
-
hf download hf://SpiderSteeped/shrink/README.md
-
curl -L -o README.md https://huggingface.co/SpiderSteeped/shrink/resolve/main/README.md
692 Bytes
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: >-
images/2025-07-03-192121_flux1-dev-fp8-e4m3fn_1234567893_res_2s_beta57_30.png
text: >-
Late 2010s smartphone photo, naturally lit with morning light spilling in
from an unseen kitchen window, captured in shallow focus with warm white
balance and slight digital grain.
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: extremely tiny mini
shrink

- Prompt
- Late 2010s smartphone photo, naturally lit with morning light spilling in from an unseen kitchen window, captured in shallow focus with warm white balance and slight digital grain.
Trigger words
You should use extremely tiny mini to trigger the image generation.
Download model
Download them in the Files & versions tab.