soyng/my-awesome-model

license: creativeml-openrail-m base_model: CompVis/stable-diffusion-v1-4 datasets:

• —None tags:
• —stable-diffusion
• —stable-diffusion-diffusers
• —text-to-image
• —diffusers inference: true ---

# Text-to-image finetuning - soyng/my-awesome-model

This pipeline was finetuned from CompVis/stable-diffusion-v1-4 on the None dataset. Below are some example images generated with the finetuned pipeline using the following prompts: High-performance car wheel rim, detailed 3D rendering:

[image]

## Pipeline usage

You can use the pipeline like so:

            from diffusers import DiffusionPipeline
            import torch
            
            pipeline = DiffusionPipeline.from_pretrained("soyng/my-awesome-model", torch_dtype=torch.float16)
            prompt = "H"
            image = pipeline(prompt).images[0]
            image.save("my_image.png")

## Training info

These are the key hyperparameters used during training:

• —Epochs: 1
• —Learning rate: 1e-05
• —Batch size: 32
• —Gradient accumulation steps: 1
• —Image resolution: 512
• —Mixed-precision: None

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