metadata

license: creativeml-openrail-m
base_model: runwayml/stable-diffusion-v1-5
datasets:
  - None
tags:
  - stable-diffusion
  - stable-diffusion-diffusers
  - text-to-image
  - diffusers
inference: true

Text-to-image finetuning - gremlin97/RemoteDiff

This pipeline was finetuned from runwayml/stable-diffusion-v1-5 on the None dataset. Below are some example images generated with the finetuned pipeline using the following prompts: ['A satellite image of a crop field']:

Pipeline usage

You can use the pipeline like so:

from diffusers import DiffusionPipeline
import torch

pipeline = DiffusionPipeline.from_pretrained("gremlin97/RemoteDiff", torch_dtype=torch.float16)
prompt = "A satellite image of a crop field"
image = pipeline(prompt).images[0]
image.save("my_image.png")

Training info

These are the key hyperparameters used during training:

Epochs: 5
Learning rate: 1e-06
Batch size: 4
Gradient accumulation steps: 4
Image resolution: 224
Mixed-precision: fp16

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