| |
|
| | --- |
| | license: creativeml-openrail-m |
| | base_model: CompVis/stable-diffusion-v1-4 |
| | datasets: |
| | - MaxReynolds/MyPatternDataset |
| | tags: |
| | - stable-diffusion |
| | - stable-diffusion-diffusers |
| | - text-to-image |
| | - diffusers |
| | inference: true |
| | --- |
| | |
| | # Text-to-image finetuning - MaxReynolds/MyStreamlitModel |
| | |
| | This pipeline was finetuned from **CompVis/stable-diffusion-v1-4** on the **MaxReynolds/MyPatternDataset** dataset. Below are some example images generated with the finetuned pipeline using the following prompts: ['<r4nd0m-l4b3l>']: |
| |
|
| |  |
| |
|
| |
|
| | ## Pipeline usage |
| |
|
| | You can use the pipeline like so: |
| |
|
| | ```python |
| | from diffusers import DiffusionPipeline |
| | import torch |
| | |
| | pipeline = DiffusionPipeline.from_pretrained("MaxReynolds/MyStreamlitModel", torch_dtype=torch.float16) |
| | prompt = "<r4nd0m-l4b3l>" |
| | image = pipeline(prompt).images[0] |
| | image.save("my_image.png") |
| | ``` |
| |
|
| | ## Training info |
| |
|
| | These are the key hyperparameters used during training: |
| |
|
| | * Epochs: 42 |
| | * Learning rate: 1e-05 |
| | * Batch size: 1 |
| | * Gradient accumulation steps: 4 |
| | * Image resolution: 512 |
| | * Mixed-precision: fp16 |
| |
|
| |
|
| | More information on all the CLI arguments and the environment are available on your [`wandb` run page](https://wandb.ai/max-f-reynolds/text2image-fine-tune/runs/su62a0vp). |
| |
|
