Text-to-Image
Diffusers
Safetensors
English
NucleusMoEImagePipeline
Mixture of Experts
sparse-moe
diffusion
image-generation
Instructions to use FenomAI/Nucleus-Image with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use FenomAI/Nucleus-Image with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("FenomAI/Nucleus-Image", 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: 887 Bytes
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"_class_name": "NucleusMoEImageTransformer2DModel",
"_diffusers_version": "0.38.0.dev0",
"patch_size": 2,
"in_channels": 64,
"out_channels": 16,
"num_layers": 32,
"attention_head_dim": 128,
"num_attention_heads": 16,
"num_key_value_heads": 4,
"joint_attention_dim": 4096,
"axes_dims_rope": [
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"mlp_ratio": 4.0,
"moe_enabled": true,
"dense_moe_strategy": "leave_first_three_blocks_dense",
"num_experts": 64,
"moe_intermediate_dim": 1344,
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"use_sigmoid": false,
"route_scale": 2.5,
"use_grouped_mm": true
}
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