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omega_IYWeBXm
thorejaya/omega_IYWeBXm
omega_IYWeBXm is a machine learning model from thorejaya. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for diffusers. The card lists the license as mit.
TAEF1 is very tiny autoencoder which uses the same "latent API" as FLUX.1's VAE. FLUX.1 is useful for real-time previewing of the FLUX.1 generation process.
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At a glance
- Library
- diffusers
- License
- mit
- Access
- Public
- Created
- Feb 7, 2025
- Updated
- Feb 7, 2025
- SHA
- 6f1e0fbc
Model card
From the Hugging Face model README
🍰 Tiny AutoEncoder for FLUX.1
TAEF1 is very tiny autoencoder which uses the same "latent API" as FLUX.1's VAE. FLUX.1 is useful for real-time previewing of the FLUX.1 generation process.
This repo contains .safetensors versions of the TAEF1 weights.
Using in 🧨 diffusers
import torch
from diffusers import FluxPipeline, AutoencoderTiny
pipe = FluxPipeline.from_pretrained(
"black-forest-labs/FLUX.1-schnell", torch_dtype=torch.bfloat16
)
pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taef1", torch_dtype=torch.bfloat16)
pipe.enable_sequential_cpu_offload()
prompt = "slice of delicious New York-style berry cheesecake"
image = pipe(
prompt,
guidance_scale=0.0,
num_inference_steps=4,
max_sequence_length=256,
).images[0]
image.save("cheesecake.png")
- Library
- diffusers
- License
- mit
- Created
- Feb 7, 2025
- Updated
- Feb 7, 2025