metadata

license: creativeml-openrail-m
library_name: diffusers
tags:
  - stable-diffusion
  - stable-diffusion-diffusers
  - text-to-image
  - diffusers
inference: true
base_model: runwayml/stable-diffusion-v1-5

Text-to-image finetuning - cosmo3769/test

This pipeline was finetuned from runwayml/stable-diffusion-v1-5 on the your_dataset_name dataset. Below are some example images generated with the finetuned pipeline using the following prompts: ['prompt1', 'prompt2', 'prompt3']:

Pipeline usage

You can use the pipeline like so:

from diffusers import DiffusionPipeline
import torch

pipeline = DiffusionPipeline.from_pretrained("cosmo3769/test", torch_dtype=torch.float16)
prompt = "prompt1"
image = pipeline(prompt).images[0]
image.save("my_image.png")

Training info

These are the key hyperparameters used during training:

Epochs: num_train_epochs
Learning rate: lr
Batch size: batch_size
Gradient accumulation steps: ga_steps
Image resolution: img_resolution
Mixed-precision: boolean

Intended uses & limitations

How to use

# TODO: add an example code snippet for running this diffusion pipeline

Limitations and bias

[TODO: provide examples of latent issues and potential remediations]

Training details

[TODO: describe the data used to train the model]