Text-to-Image
Diffusers
Safetensors
flow-matching
pyramidal-unet
256x256
ettin-150m
from-scratch
ra
udit
Instructions to use AiArtLab/Ra with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AiArtLab/Ra with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("AiArtLab/Ra", 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
Commit History
Today
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publish.py: new repo id
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Card: link the upstream autoencoder and text encoder
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Card: why the pyramid (11x less compute)
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Card: butterflies first (validated), then FLUX-Reason
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Card: compact
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Card: shorter, butterfly samples, training in progress
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Ra fp16 (step 212000)
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remove probe
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Ra: card
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Upload hf_probe.txt with huggingface_hub
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initial commit
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