Text-to-Image
Diffusers
Safetensors
image-generation
flow-matching
ideogram4
distillation
cfg-distillation
no-cfg
fast
20-step
fp4
nvfp4
quantization-aware-distillation
Instructions to use fal/ideogram-v4-fast with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fal/ideogram-v4-fast with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fal/ideogram-v4-fast", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Demo for this model on Spaces
#1
by multimodalart - opened
Hi friends!
As some of you know, I'm Apolinario, from the open-source team at Hugging Face. Congrats and thanks for open-sourcing fal/ideogram-v4-fast on the Hub! We were excited about this work and built with an agent an interactive demo app of it on Hugging Face Spaces, running on a free ZeroGPU infrastructure.
Here's a link to the demo: https://huggingface.co/spaces/hugging-apps/ideogram-v4-fast-demo
We would love to transfer this demo to you or your org if it makes sense. Would you like this demo to live under your own account or organization?
(If you have any questions or just want to chat more about this, just hit me up on our shared Slack)
Cheers,
Poli
multimodalart changed discussion status to closed
@gokaygokay for vis