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jimmycarter/flux-training-losercity-next-lycoris2
flux-training-losercity-next-lycoris2 is a text-to-image model from jimmycarter. Use it when you need an image from a text prompt. It is set up for diffusers. The card lists the license as other.
This is a LyCORIS adapter derived from black-forest-labs/FLUX.1-dev.
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.safetensors350 MB · 99%
From the Hugging Face model README
This is a LyCORIS adapter derived from black-forest-labs/FLUX.1-dev.
The main validation prompt used during training was:
loona from helluva boss is eating a donut
3.50.015None421024Note: The validation settings are not necessarily the same as the training settings.
You can find some example images in the following gallery:
<Gallery />The text encoder was not trained. You may reuse the base model text encoder for inference.
{
"algo": "lokr",
"multiplier": 1.0,
"linear_dim": 1000000,
"linear_alpha": 1,
"factor": 10,
"apply_preset": {
"target_module": [
"FluxTransformer2DModel"
]
}
}
import torch
from diffusers import DiffusionPipeline
from lycoris import create_lycoris_from_weights
model_id = 'black-forest-labs/FLUX.1-dev'
adapter_id = 'pytorch_lora_weights.safetensors' # you will have to download this manually
lora_scale = 1.0
wrapper, _ = create_lycoris_from_weights(lora_scale, adapter_id, pipeline.transformer)
wrapper.merge_to()
prompt = "loona from helluva boss is eating a donut"
pipeline.to('cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu')
image = pipeline(
prompt=prompt,
num_inference_steps=15,
generator=torch.Generator(device='cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu').manual_seed(1641421826),
width=1024,
height=1024,
guidance_scale=3.5,
).images[0]
image.save("output.png", format="PNG")