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뉴스, 도구, 모델, 가이드, 주제, 워크플로, 프롬프트를 함께 검색합니다.

AI 모델 298

“Stable Diffusion API”

AI 모델StableDiffusionVN

Flux

StableDiffusionVN · license:apache-2.0모델 보기 ↗
AI 모델gpustack

stable-diffusion-xl-base-1.0-GGUF

**Model creator**: Stability AI **Original model**: stable-diffusion-xl-base-1.0 **GGUF quantization**: based on stable-diffusion.cpp ac54e that patched by llama-box. **VAE From**: madebyollin/sdxl-vae-fp16-fix. SDXL consists of an ensemble of experts pipeline for latent diffusion: In a first step, the base model is used to generate (noisy) latents, which are then further processed with a refinement model (available here: https://huggingface.co/stabilityai/stable-diffusion-xl-refiner-1.0/) specialized for the final denoising steps. Note that the base model can be used as a standalone module. Alternatively, we can use a two-stage pipeline as follows: First, the base model is used to generate latents of the desired output size. In the second step, we use a specialized high-resolution model and apply a technique called SDEdit (https://arxiv.org/abs/2108.01073, also known as "img2img") to the latents generated in the first step, using the same prompt. This technique is slightly slower than the first one, as it requires more function evaluations.

gpustack · license:openrail++모델 보기 ↗
AI 모델Peter-jz

stable-diffusion-3.5-large-DF11

Peter-jz모델 보기 ↗
AI 모델gaianet

stable-diffusion-3.5-medium-GGUF

gaianet · license:other모델 보기 ↗
AI 모델lllyasviel

control_v11p_sd15_mlsd

**Controlnet v1.1** is the successor model of Controlnet v1.0 and was released in lllyasviel/ControlNet-v1-1 by Lvmin Zhang. This checkpoint is a conversion of the original checkpoint into `diffusers` format. It can be used in combination with **Stable Diffusion**, such as runwayml/stable-diffusion-v1-5. @misc{zhang2023adding, title={Adding Conditional Control to Text-to-Image Diffusion Models}, author={Lvmin Zhang and Maneesh Agrawala}, year={2023}, eprint={2302.05543}, archivePrefix={arXiv}, primaryClass={cs.CV} }

lllyasviel · license:openrail모델 보기 ↗
AI 모델leejet

FLUX.1-schnell-gguf

The license of the quantized files follows the license of the original model: - FLUX.1-schnell: apache-2.0 Run FLUX using stable-diffusion.cpp with a GPU that has 6GB or even 4GB of VRAM: https://github.com/leejet/stable-diffusion.cpp/blob/master/docs/flux.md

leejet · license:apache-2.0모델 보기 ↗
AI 모델Comfy-Org

stable-diffusion-1.5

This is an archival re-upload of Stable Diffusion v1.5, originally at https://huggingface.co/runwayml/stable-diffusion-v1-5 until RunwayML took down that page. This model is from 2022, and is several major generational upgrades behind, it is being preserved here for technical & accessibility reasons (eg legacy model testing). https://huggingface.co/Comfy-Org/stable-diffusion-v1-5-archive/blob/main/v1-5-pruned-emaonly.safetensors is the exact original hash-identical model as uploaded by RunwayML.

Comfy-Org · license:creativeml-openrail-m모델 보기 ↗
AI 모델Stability AI

stable-diffusion-3-medium-tensorrt

Stability AI · license:other모델 보기 ↗
AI 모델optimum-intel-internal-testing

tiny-random-stable-diffusion-xl-refiner

optimum-intel-internal-testing · license:apache-2.0모델 보기 ↗
AI 모델ashawkey

zero123-xl-diffusers

_Note: This section is originally taken from the Stable Diffusion v2 model card, but applies in the same way to Zero-1-to-3._ The model is intended for research purposes only. Possible research areas and tasks include: - Safe deployment of large-scale models. - Probing and understanding the limitations and biases of generative models. - Generation of artworks and use in design and other artistic processes. - Applications in educational or creative tools. - Research on generative models.

ashawkey · license:mit모델 보기 ↗