Text-to-image finetuning - rohith2812/atoi-finetuned-model
This pipeline was finetuned from stable-diffusion-v1-5/stable-diffusion-v1-5 on the rohith2812/atoi-finetuning dataset. Below are some example images generated with the finetuned pipeline using the following prompts: ['A picture of a cat explaining linear regression']:
Pipeline usage
You can use the pipeline like so:
from diffusers import DiffusionPipeline
import torch
pipeline = DiffusionPipeline.from_pretrained("rohith2812/atoi-finetuned-model", torch_dtype=torch.float16)
prompt = "A picture of a cat explaining linear regression"
image = pipeline(prompt).images[0]
image.save("my_image.png")
Training info
These are the key hyperparameters used during training:
- Epochs: 4
- Learning rate: 1e-05
- Batch size: 1
- Gradient accumulation steps: 4
- Image resolution: 256
- 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]
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Model tree for rohith2812/atoi-finetuned-model
Base model
stable-diffusion-v1-5/stable-diffusion-v1-5