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smartguy0505
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tae

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Diffusers library
# Gated model: Login with a HF token with gated access permission
hf auth login
pip install -U diffusers transformers accelerate
import torch
from diffusers import DiffusionPipeline

# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("smartguy0505/tae", dtype=torch.bfloat16, device_map="cuda")

prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]

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🍰 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("smartguy0505/tae", 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")

image/jpeg

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