aditya11997/kandi2-decoder-3.1

license: creativeml-openrail-m base_model: kandinsky-community/kandinsky-2-2-decoder datasets:

• —kbharat7/DogChestXrayDatasetNew prior:
• —kandinsky-community/kandinsky-2-2-prior tags:
• —kandinsky
• —text-to-image
• —diffusers
• —diffusers-training inference: true ---

Finetuning - aditya11997/kandi2-decoder-3.1

This pipeline was finetuned from kandinsky-community/kandinsky-2-2-decoder on the kbharat7/DogChestXrayDatasetNew dataset. Below are some example images generated with the finetuned pipeline using the following prompts: ['photo of dogxraysmall']:

[image]

Pipeline usage

You can use the pipeline like so:

from diffusers import DiffusionPipeline
import torch

pipeline = AutoPipelineForText2Image.from_pretrained("aditya11997/kandi2-decoder-3.1", torch_dtype=torch.float16)
prompt = "photo of dogxraysmall"
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: 1
• —Gradient accumulation steps: 4
• —Image resolution: 768
• —Mixed-precision: None