Instructions to use VirtualAddressExtension/Neta-Lumina-v1.0-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use VirtualAddressExtension/Neta-Lumina-v1.0-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("VirtualAddressExtension/Neta-Lumina-v1.0-diffusers", 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: 508 Bytes
dc6091d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 | {
"_class_name": "Lumina2Transformer2DModel",
"_diffusers_version": "0.34.0",
"axes_dim_rope": [
32,
32,
32
],
"axes_lens": [
300,
512,
512
],
"cap_feat_dim": 2304,
"ffn_dim_multiplier": null,
"hidden_size": 2304,
"in_channels": 16,
"multiple_of": 256,
"norm_eps": 1e-05,
"num_attention_heads": 24,
"num_kv_heads": 8,
"num_layers": 26,
"num_refiner_layers": 2,
"out_channels": null,
"patch_size": 2,
"sample_size": 128,
"scaling_factor": 1.0
}
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