Instructions to use diffusers-internal-dev/private-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use diffusers-internal-dev/private-model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("diffusers-internal-dev/private-model", 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
- Draw Things
- DiffusionBee
File size: 389 Bytes
efb94c3 6c79908 efb94c3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | {
"_class_name": "SD3Transformer2DModel",
"_diffusers_version": "0.28.0.dev0",
"_name_or_path": "diffusers/diffusers_sd3",
"attention_head_dim": 64,
"caption_projection_dim": 1152,
"cross_attention_dim": 4096,
"in_channels": 16,
"num_attention_heads": 18,
"num_layers": 18,
"out_channels": 16,
"patch_size": 2,
"pooled_projection_dim": 2048,
"sample_size": 128
}
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