Text-to-Image
Diffusers
Safetensors
English
FluxPipeline
Flux
FluxPipeline
flux dev
flux de-distilled
image-generation
flux-diffusers
photo
realism
Instructions to use AlekseyCalvin/VerusVision1b_Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AlekseyCalvin/VerusVision1b_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("AlekseyCalvin/VerusVision1b_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
- Draw Things
- DiffusionBee
File size: 392 Bytes
d891e07 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | {
"_class_name": "FluxTransformer2DModel",
"_diffusers_version": "0.30.0.dev0",
"_name_or_path": "../checkpoints/flux-dev/transformer",
"attention_head_dim": 128,
"guidance_embeds": true,
"in_channels": 64,
"joint_attention_dim": 4096,
"num_attention_heads": 24,
"num_layers": 19,
"num_single_layers": 38,
"patch_size": 1,
"pooled_projection_dim": 768
}
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