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arpachat/output-fashion-400

sourceHugging Facecreativeml-openrail-mupdated 3y agoView on Hugging Face

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Model Card

license: creativeml-openrail-m base_model: OFA-Sys/small-stable-diffusion-v0 datasets:

—jwl25b/finalprojectdataset tags:
—stable-diffusion
—stable-diffusion-diffusers
—text-to-image
—diffusers inference: true ---

Text-to-image finetuning - arpachat/output-fashion-400

This pipeline was finetuned from OFA-Sys/small-stable-diffusion-v0 on the jwl25b/final_project_dataset dataset. Below are some example images generated with the finetuned pipeline using the following prompts: ['Blue Tommy Hilfiger jacket']:

[image]

Pipeline usage

You can use the pipeline like so:

python

from diffusers import DiffusionPipeline
import torch

pipeline = DiffusionPipeline.from_pretrained("arpachat/output-fashion-400", torch_dtype=torch.float16)
prompt = "Blue Tommy Hilfiger jacket"
image = pipeline(prompt).images[0]
image.save("my_image.png")

Training info

These are the key hyperparameters used during training:

—Epochs: 58
—Learning rate: 1e-05
—Batch size: 4
—Gradient accumulation steps: 2
—Image resolution: 512
—Mixed-precision: fp16

More information on all the CLI arguments and the environment are available on your `wandb` run page.