Instructions to use optimum-internal-testing/tiny-random-flux with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use optimum-internal-testing/tiny-random-flux with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("optimum-internal-testing/tiny-random-flux", 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: 509 Bytes
ebaf8d4 d64d988 ebaf8d4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | {
"_class_name": "FluxTransformer2DModel",
"_diffusers_version": "0.31.0",
"_name_or_path": "/home/user/.cache/huggingface/hub/models--katuni4ka--tiny-random-flux/snapshots/36abdcc25faf1a91425f0e38ffa8b5d427534cef/transformer",
"attention_head_dim": 16,
"axes_dims_rope": [
4,
4,
8
],
"guidance_embeds": true,
"in_channels": 4,
"joint_attention_dim": 32,
"num_attention_heads": 2,
"num_layers": 1,
"num_single_layers": 1,
"patch_size": 1,
"pooled_projection_dim": 32
}
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