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Euler: "Basic Steps" or "Simple Subtraction" - This sampler works by simply removing noise in each step. It's like taking away a layer of blur to reveal the image. It is also one of the fastest and most straightforward samplers 

Euler a: "Creative Variation" or "Adding Noise" – This one is like the "Basic Steps" sampler, but with a bit of random noise added back in at each step. This makes the results more unpredictable, like a creative filter that produces a slightly different image each time [2, 3]. This also means that the image will keep changing as more steps are added [4, 5].

DPM2: "Smart Prediction" - This sampler uses a smarter way to predict how to remove the noise, making it more accurate [6].

DPM2 Karras: "Smart Prediction, Better Colors" – Like the previous one but with improved color quality.

DPM++ 2M: "Advanced Smart Prediction" – An improved version of "Smart Prediction" that uses some extra information from previous steps to make better predictions [6, 7].

DPM++ 2M Karras: "Advanced Smart Prediction, Better Colors" – Like the previous one but with improved color quality [6, 7].

DPM++ SDE: "Detailed Stochastic Prediction" – This sampler uses a more complex math model to understand noise, resulting in detailed images [7]. It is stochastic, meaning that it introduces a degree of randomness, which can lead to varied results [8].

DPM++ SDE Karras: "Optimized Detailed Stochastic Prediction" - This is a version of the previous sampler that is optimized for better performance and image quality [7].

DPM fast: "Fast DPM" - This sampler is designed to be fast, but may require more steps and is not generally recommended [9-11].

DPM adaptive: "Self-Adjusting Detail" - Instead of using steps, this sampler adjusts itself based on a setting that changes the image's contrast and saturation [4, 12].

Heun: "Two-Step Correction" - This sampler works by predicting the image, checking the prediction, and then combining both for a better result [13]. It uses a weighted average of two noise estimates [14].

LMS: "Artistic Style" or "Painterly" – This sampler uses information from previous steps to create an image with a more artistic or painterly style [15]. It can struggle with generating detailed characters or animals [16].

LMS Karras: "Artistic Style, Better Colors" – Like the previous one but with improved color quality [16].

DDIM: "Photorealistic Detail" or "Smooth Solver" – This sampler uses a special method to generate images which are often photorealistic and highly detailed. It was widely used, but is now considered outdated by some [17, 18].

PLMS: "Quick Estimator" – This sampler quickly estimates the noise and removes it, but it is not generally recommended because it is slower and produces worse results [9, 19].

LCM: "Fast Refiner" or "Single Step Image" – This sampler can produce good images very quickly, in as little as one step. It uses a special technique to refine the image in its latent space [20].

Restart: "Noise Reset" or "Iterative Correction" - This sampler is like restarting the image generation by adding a lot of noise, and then starting again with the denoising process. It does this several times [21, 22].

UniPC: "Smart Combination" or "Flexible Solver" – This sampler is designed to combine information in a way that it can be used with many different models. It can also change its level of accuracy to work faster [23].

Thread to compile known character LoRAs