<img src="https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/6ab02e8a-1e96-46e0-b3f3-e7f72d8ec086/width=525/6ab02e8a-1e96-46e0-b3f3-e7f72d8ec086.jpeg" />Training data here : <a target="_blank" rel="ugc" href="https://huggingface.co/datasets/codeShare/lora-training-data/tree/main">https://huggingface.co/datasets/codeShare/lora-training-data/tree/main</a>LoRa trained with Sigma memes. 10 repeats x 30 epochs x 25 steps = 7500 stepsTry writing some text in your output images. It helps guide the output a lot!//---//I could probably write a bit here on how to use the LoRa , but I think the easiest option is to just look at the training data in the link above and adapt your prompting style accordingly.//--//Use JoyCaption : <a target="_blank" rel="ugc" href="https://huggingface.co/spaces/fancyfeast/joy-caption-alpha-two">https://huggingface.co/spaces/fancyfeast/joy-caption-alpha-two</a>Saves a lot of time writing a long prompt. If you run out of Huggingface GPU resources feel free to run the joycaption notebook on Colab: <a target="_blank" rel="ugc" href="https://colab.research.google.com/github/camenduru/joy-caption-jupyter/blob/main/joy_caption_jupyter.ipynb">https://colab.research.google.com/github/camenduru/joy-caption-jupyter/blob/main/joy_caption_jupyter.ipynb</a>

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