Instructions to use WaveCut/ideogram-4-sdnq-uint4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WaveCut/ideogram-4-sdnq-uint4 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("WaveCut/ideogram-4-sdnq-uint4", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
File size: 523 Bytes
f3d279e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | {
"_class_name": "Ideogram4Transformer2DModel",
"_diffusers_version": "0.39.0.dev0",
"_name_or_path": "/home/jinli/.cache/huggingface/hub/models--ideogram-ai--debug-ideogram-v4/snapshots/41af6183c9fd9b6254864b0720319ef984535bfc/transformer",
"adaln_dim": 512,
"attention_head_dim": 256,
"in_channels": 128,
"intermediate_size": 12288,
"llm_features_dim": 53248,
"mrope_section": [
24,
20,
20
],
"norm_eps": 1e-05,
"num_attention_heads": 18,
"num_layers": 34,
"rope_theta": 5000000
}
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