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histin116/agar-4-nogarmentdescription
agar-4-nogarmentdescription is a text-to-image model from histin116. Use it when you need an image from a text prompt. It is set up for diffusers. The card lists the license as creativeml-openrail-m.
This is a LoRA derived from black-forest-labs/FLUX.1-dev.
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From the Hugging Face model README
This is a LoRA derived from black-forest-labs/FLUX.1-dev.
The main validation prompt used during training was:
A young man riding a horse, wearing a loose-fitting, short-sleeved, button-up shirtThe shirt features a mix of monochromatic tones with prominent blue accents. The central design on the shirt seems to be a surreal, abstract figure or face, with its eyes obscured by a bold, horizontal blue line. The rest of the shirt has various patterns and images that resemble a collage, including what looks like newspaper print on one of the sleeves.
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.
import torch
from diffusers import DiffusionPipeline
model_id = 'black-forest-labs/FLUX.1-dev'
adapter_id = 'histin116/agar-4-nogarmentdescription'
pipeline = DiffusionPipeline.from_pretrained(model_id)
pipeline.load_lora_weights(adapter_id)
prompt = "A young man riding a horse, wearing a loose-fitting, short-sleeved, button-up shirtThe shirt features a mix of monochromatic tones with prominent blue accents. The central design on the shirt seems to be a surreal, abstract figure or face, with its eyes obscured by a bold, horizontal blue line. The rest of the shirt has various patterns and images that resemble a collage, including what looks like newspaper print on one of the sleeves."
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")