Text-to-Image
Diffusers
Safetensors
Ideogram4Pipeline
image-generation
diffusion
flow-matching
dit
ideogram
Instructions to use ideogram-ai/ideogram-4-fp8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ideogram-ai/ideogram-4-fp8 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") 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
Why "red apple* would trigger safety filter?
#23
by wfen - opened
Does Ideogram make this model unusable intentionally?
are you using natural prompts with ideogram or json format prompts?
Here is what I observed:
- Safety filter fires randomly on completely safe prompts
Observation
The built-in safety filter is non-deterministic and false-positives
frequently. The same 100% benign prompt:
"A red apple on a wooden table, soft natural light"
was submitted 7 times and returned the grey "Image blocked by safety
filter" card 6 times (~86% false-positive rate):
quality=medium -> blocked
quality=high -> blocked
run 1 -> blocked
run 2 -> blocked
run 3 -> blocked
run 4 -> PASSED (real image)
run 5 -> blocked
For each run I spend nearly 1 mins, and this safety filter only shows up at the very end, ensure the user really has spent their inference cost.