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Nano SD Tuned Sample 1

Model tuned untuk eksperimen text-to-image.

license: creativeml-openrail-m base_model: lambdalabs/miniSD-diffusers datasets: - kopyl/833-icons-dataset-1024-blip-large tags: - stable-diffusion - stable-diffusion-diffusers - text-to-image - diffusers inference: true

Text-to-image finetuning - kopyl/nano-sd-tuned-sample

This pipeline was finetuned from lambdalabs/miniSD-diffusers on the kopyl/833-icons-dataset-1024-blip-large dataset. Below are some example images generated with the finetuned pipeline using the following prompts: ['photo of a frog']:

Pipeline usage

You can use the pipeline like so:

from diffusers import DiffusionPipeline
import torch

pipeline = DiffusionPipeline.from_pretrained("kopyl/nano-sd-tuned-sample", torch_dtype=torch.float16)
prompt = "photo of a frog"
image = pipeline(prompt).images[0]
image.save("my_image.png")

Training info

These are the key hyperparameters used during training:

Epochs: 1
Learning rate: 1e-05
Batch size: 1
Gradient accumulation steps: 1
Image resolution: 256
Mixed-precision: fp16

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

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