Text-to-Image
Diffusers
lora
ideogram4
style
vintage
film
vhs
found-footage
1990s
industrial
retro
ps2
low-poly
game-screenshot
2004
vertex-lighting
interlacing
template:diffusion-lora
Instructions to use jmanhype/Ideogram-4.0-LoRAs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jmanhype/Ideogram-4.0-LoRAs with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ideogram-ai/ideogram-4-fp8", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("jmanhype/Ideogram-4.0-LoRAs") prompt = "VHS_RALLY_95 - 1995 Hi8 camcorder found footage aesthetic" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download example_dog.png from jmanhype/Ideogram-4.0-LoRAs: direct link, hf CLI and curl.
- Browser
- Download file 1.57 MB
-
https://huggingface.co/jmanhype/Ideogram-4.0-LoRAs/resolve/main/example_dog.png
- Command line
-
hf download hf://jmanhype/Ideogram-4.0-LoRAs/example_dog.png
-
curl -L -o example_dog.png https://huggingface.co/jmanhype/Ideogram-4.0-LoRAs/resolve/main/example_dog.png
1.57 MB

- Xet hash:
- d373d22510b7fbfdbf19fd84a5f22c989f389247b79cf141eba21f7d90e165a2
- Size of remote file:
- 1.57 MB
- SHA256:
- c6f3d72640026ba0afaf93fb12e10362f7e97b37ca26480c8abce02ae526b0d7
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