metadata
license: creativeml-openrail-m
library_name: diffusers
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
- diffusers-training
inference: true
base_model: CompVis/stable-diffusion-v1-4
Text-to-image finetuning - BlackSadadou/SD-Black-IMGgen-Model-v2
This pipeline was finetuned from CompVis/stable-diffusion-v1-4 on the BlackSadadou/STBlackIMGgen dataset. Below are some example images generated with the finetuned pipeline using the following prompts: ["Illustration graphique d'un Chat dans le style 'BLACK's Style'."]:
Pipeline usage
You can use the pipeline like so:
from diffusers import DiffusionPipeline
import torch
pipeline = DiffusionPipeline.from_pretrained("BlackSadadou/SD-Black-IMGgen-Model-v2", torch_dtype=torch.float16)
prompt = "Illustration graphique d'un Chat dans le style 'BLACK's Style'."
image = pipeline(prompt).images[0]
image.save("my_image.png")
Training info
These are the key hyperparameters used during training:
- Epochs: 417
- Learning rate: 1e-05
- Batch size: 1
- Gradient accumulation steps: 4
- Image resolution: 512
- Mixed-precision: fp16
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]