Progamergov
Models by this creator
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knollingcase-embeddings-sd-v2-0
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The knollingcase-embeddings-sd-v2-0 is a set of text embeddings trained by ProGamerGov for use with the Stable Diffusion v2.0 model. These embeddings are designed to produce images with a "knollingcase" style, which is described as a concept inside a sleek, sometimes sci-fi, display case with transparent walls and a minimalistic background. The embeddings were trained through several iterations, with the v4 version using 116 high-quality training images and producing the best results. Other similar models like the Double-Exposure-Embedding and Min-Illust-Background-Diffusion also aim to produce unique artistic styles for Stable Diffusion. Model inputs and outputs Inputs Text prompts using the provided "knollingcase" trigger words (e.g. "kc8", "kc16", "kc32") to activate the embedding Outputs Images in the "knollingcase" style, with a concept or object displayed in a sleek, futuristic case Capabilities The knollingcase-embeddings-sd-v2-0 model excels at generating highly detailed, photorealistic images with a distinct sci-fi or minimalistic aesthetic. The transparent display case and clean background create a striking visual effect that sets the generated images apart. What can I use it for? This model could be valuable for creating product visualizations, conceptual art, or promotional imagery with a futuristic, high-tech feel. The diverse range of prompts and the ability to fine-tune the style through the various embedding versions provide a lot of creative flexibility. Things to try Experiment with different prompt structures that incorporate the "knollingcase" trigger words, such as: "A highly detailed, photorealistic [CONCEPT], encased in a transparent, minimalist display, kc32-v4-5000" "A [CONCEPT] inside a sleek, sci-fi case, very detailed, kc16-v4-5000" "A [CONCEPT] in a futuristic, transparent display, kc8-v4-5000" Try using different samplers like DPM++ SDE Karras or DPM++ 2S a Karras, as suggested by the maintainer, to see how they affect the output.
Updated 5/28/2024
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Min-Illust-Background-Diffusion
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The Min-Illust-Background-Diffusion model is a fine-tuned version of the Stable Diffusion v1.5 model, trained by ProGamerGov on a selection of artistic works by Sin Jong Hun. This model was trained for 2250 iterations with a batch size of 4, using the ShivamShrirao/diffusers library with full precision, prior-preservation loss, the train-text-encoder feature, and the new 1.5 MSE VAE from Stability AI. A total of 4120 regularization / class images were used from this dataset. Similar models like the Vintedois (22h) Diffusion model and the Stable Diffusion v1-4 model also use Stable Diffusion as a base, but are trained on different datasets and have their own unique characteristics. Model inputs and outputs Inputs Prompt: A text description that the model uses to generate the output image. The model responds best to prompts that include the token **sjh style. Outputs Image**: A generated image that matches the prompt. The model outputs images at 512x512, 512x768, and 512x512 resolutions. Capabilities The Min-Illust-Background-Diffusion model is capable of generating artistic, landscape-style images that capture the aesthetic of the training data. The model performs well on prompts that steer the output towards specific artistic styles, even at a weaker strength. However, the model is not as well-suited for generating portraits and related tasks, as the training data was primarily composed of landscapes. What can I use it for? This model could be useful for projects that require the generation of landscape-style artwork, such as concept art, background designs, or illustrations. The ability to fine-tune the artistic style through prompt engineering makes it a flexible tool for creative applications. However, due to the limitations around portrait generation, this model may not be the best choice for projects that require realistic human faces or characters. For those use cases, other Stable Diffusion-based models like Stable Diffusion v1-4 may be a better fit. Things to try One interesting aspect of this model is its ability to capture specific artistic styles through the use of the sjh style token in the prompt. Experimentation with this token and other style-specific keywords could lead to the generation of unique, visually striking artwork. Additionally, exploring the model's ability to generate landscape-focused images with different perspectives, compositions, and lighting conditions could reveal its versatility and lead to the creation of compelling visual assets.
Updated 5/27/2024
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360-Diffusion-LoRA-sd-v1-5
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The 360-Diffusion-LoRA-sd-v1-5 model is a fine-tuned Stable Diffusion v1-5 model developed by ProGamerGov that has been trained on an extremely diverse dataset of 2,104 captioned 360 equirectangular projection images. This model was fine-tuned with the trigger word qxj, and is intended to be used with the AUTOMATIC1111 WebUI by appending `` to the prompt. The model differs from similar fine-tuned Stable Diffusion models like Mo Di Diffusion, Hitokomoru Diffusion, and Epic Diffusion in its specialized focus on 360 degree equirectangular projection images across a wide range of photographic styles and subjects. Model inputs and outputs Inputs Textual prompts that can include the trigger word qxj and the AUTOMATIC1111 WebUI tag `` to activate the model Outputs 360 degree equirectangular projection images in a variety of photographic styles and subjects, including scenes, landscapes, and portraits Capabilities The 360-Diffusion-LoRA-sd-v1-5 model is capable of generating high-quality 360 degree equirectangular projection images across a wide range of photographic styles and subjects. The model can produce images ranging from architectural renderings and digital illustrations to natural landscapes and science fiction scenes. Some examples include a castle sketch, a sci-fi cockpit, a tropical beach photo, and a guy standing. What can I use it for? The 360-Diffusion-LoRA-sd-v1-5 model can be useful for a variety of applications that require 360 degree equirectangular projection images, such as virtual reality experiences, panoramic photography, and immersive multimedia content. Creators and developers working in these areas may find this model particularly useful for generating high-quality, photorealistic 360 degree images to incorporate into their projects. Things to try One interesting aspect of the 360-Diffusion-LoRA-sd-v1-5 model is the wide variety of styles and subjects it can generate, from realistic photographic scenes to more fantastical and imaginative compositions. Experimenting with different prompts, combining the model with other fine-tuned Stable Diffusion models, and exploring the various "useful tags" provided by the maintainer could lead to some unique and unexpected results.
Updated 9/6/2024