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…
Open weights
openrail++
2.6B parameters
diffusers
Modifications to the original model card are in red or green Stable Diffusion is a latent text-to-image diffusion model capable of generating photo-realistic images given any text input. For more information about how Stable Diffusion functions, please have a look at 's Stable Diffusion blog. The Stable-Diffusion-v1-5 checkpoint was initialized with the weights of the Stable-Diffusion-v1-2 checkpoint and subsequently fine-tuned on 595k steps at resolution 512x512 on "laion-aesthetics v2 5+" and 10% dropping of the text-conditioning to improve classifier-free guidance sampling. You can use this both with the Diffusers library and RunwayML GitHub repository ( now deprecated ), ComfyUI…
Open weights
creativeml-openrail-m
860M parameters
diffusers
Model · Text to image
Lykon
lykon/dreamshaper-7 is a Stable Diffusion model that has been fine-tuned on runwayml/stable-diffusion-v1-5. For more general information on how to run text-to-image models with Diffusers, see the docs. - Version 8 focuses on improving what V7 started. Might be harder to do photorealism compared to realism focused models, as it might be hard to do anime compared to anime focused models, but it can do both pretty well if you're skilled enough. Check the examples! - Version 7 improves lora support, NSFW and realism. If you're interested in "absolute" realism, try AbsoluteReality. - Version 6 adds more lora support and more style in general. It should also be better at generating directly at…
Open weights
creativeml-openrail-m
860M parameters
diffusers
FLUX.1 [dev] is a 12 billion parameter rectified flow transformer capable of generating images from text descriptions. For more information, please read our blog post. 1. Cutting-edge output quality, second only to our state-of-the-art model FLUX.1 [pro]. 2. Competitive prompt following, matching the performance of closed source alternatives. 3. Trained using guidance distillation, making FLUX.1 [dev] more efficient. 4. Open weights to drive new scientific research, and empower artists to develop innovative workflows. 5. Generated outputs can be used for personal, scientific, and commercial purposes as described in the [FLUX.1 [dev] Non-Commercial…
Access requested at publisher
other
11.9B parameters
diffusers
SDXL-Turbo is a fast generative text-to-image model that can synthesize photorealistic images from a text prompt in a single network evaluation. A real-time demo is available here: http://clipdrop.co/stable-diffusion-turbo Please note: For commercial use, please refer to https://stability.ai/license. SDXL-Turbo is a distilled version of SDXL 1.0, trained for real-time synthesis. SDXL-Turbo is based on a novel training method called Adversarial Diffusion Distillation (ADD) (see the technical report), which allows sampling large-scale foundational image diffusion models in 1 to 4 steps at high image quality. This approach uses score distillation to leverage large-scale off-the-shelf image…
Open weights
other
2.6B parameters
diffusers
FLUX.1 [schnell] is a 12 billion parameter rectified flow transformer capable of generating images from text descriptions. For more information, please read our blog post. 1. Cutting-edge output quality and competitive prompt following, matching the performance of closed source alternatives. 2. Trained using latent adversarial diffusion distillation, FLUX.1 [schnell] can generate high-quality images in only 1 to 4 steps. 3. Released under the apache-2.0 licence, the model can be used for personal, scientific, and commercial purposes. We provide a reference implementation of FLUX.1 [schnell], as well as sampling code, in a dedicated github repository. Developers and creatives looking to…
Access requested at publisher
apache-2.0
11.9B parameters
diffusers
Welcome to the official repository for the Z-Image（造相）project! Z-Image is a powerful and highly efficient image generation model family with 6B parameters. Currently there are four variants: - Z-Image-Turbo – A distilled version of Z-Image that matches or exceeds leading competitors with only 8 NFEs (Number of Function Evaluations). It offers sub-second inference latency on enterprise-grade H800 GPUs and fits comfortably within 16G VRAM consumer devices. It excels in photorealistic image generation, bilingual text rendering (English & Chinese), and robust instruction adherence. - Z-Image – The foundation model behind Z-Image-Turbo. Z-Image focuses on high-quality generation, rich…
Open weights
apache-2.0
6.2B parameters
diffusers
Stable Diffusion is a latent text-to-image diffusion model capable of generating photo-realistic images given any text input. For more information about how Stable Diffusion functions, please have a look at 's Stable Diffusion with Diffusers blog. The Stable-Diffusion-v1-4 checkpoint was initialized with the weights of the Stable-Diffusion-v1-2 checkpoint and subsequently fine-tuned on 225k steps at resolution 512x512 on "laion-aesthetics v2 5+" and 10% dropping of the text-conditioning to improve classifier-free guidance sampling. This weights here are intended to be used with the Diffusers library. If you are looking for the weights to be loaded into the CompVis Stable Diffusion codebase…
Open weights
creativeml-openrail-m
860M parameters
diffusers
Animagine XL 4.0, also stylized as Anim4gine, is the ultimate anime-themed finetuned SDXL model and the latest installment of Animagine XL series. Despite being a continuation, the model was retrained from Stable Diffusion XL 1.0 with a massive dataset of 8.4M diverse anime-style images from various sources with the knowledge cut-off of January 7th 2025 and finetuned for approximately 2650 GPU hours. Similar to the previous version, this model was trained using tag ordering method for the identity and style training. With the release of Animagine XL 4.0 Opt (Optimized), the model has been further refined with an additional dataset, improving stability, anatomy accuracy, noise reduction…
Open weights
openrail++
2.6B parameters
diffusers
SD-Turbo is a fast generative text-to-image model that can synthesize photorealistic images from a text prompt in a single network evaluation. We release SD-Turbo as a research artifact, and to study small, distilled text-to-image models. For increased quality and prompt understanding, we recommend SDXL-Turbo. Please note: For commercial use, please refer to https://stability.ai/license. SD-Turbo is a distilled version of Stable Diffusion 2.1, trained for real-time synthesis. SD-Turbo is based on a novel training method called Adversarial Diffusion Distillation (ADD) (see the technical report), which allows sampling large-scale foundational image diffusion models in 1 to 4 steps at high…
Open weights
866M parameters
diffusers
Model · Text to image
Qwen
We are thrilled to release Qwen-Image, an image generation foundation model in the Qwen series that achieves significant advances in complex text rendering and precise image editing. Experiments show strong general capabilities in both image generation and editing, with exceptional performance in text rendering, especially for Chinese. - 2025.08.04: We released the Technical Report of Qwen-Image! - 2025.08.04: We released Qwen-Image weights! Check at huggingface and Modelscope! - 2025.08.04: We released Qwen-Image! Check our blog for more details! Install the latest version of diffusers The following contains a code snippet illustrating how to use the model to generate images based on text…
Open weights
apache-2.0
20.4B parameters
diffusers
This repository contains a model that generates highly aesthetic images of resolution 1024x1024, as well as portrait and landscape aspect ratios. You can use the model with Hugging Face Diffusers. Playground v2.5 is a diffusion-based text-to-image generative model, and a successor to Playground v2. Playground v2.5 is the state-of-the-art open-source model in aesthetic quality. Our user studies demonstrate that our model outperforms SDXL, Playground v2, PixArt-α, DALL-E 3, and Midjourney 5.2. For details on the development and training of our model, please refer to our blog post and technical report. Install diffusers >= 0.27.0 and the relevant dependencies. - The pipeline uses the…
Open weights
other
2.6B parameters
diffusers
/ FIXED: Changed from 50% to 33.33% because there are 3 columns / margin-bottom: 1em; / Added small margin for spacing between stacked images / font-weight: bold; / Corrected 'font-style: bold' to 'font-weight: bold' / } / FIXED: Added missing closing brace here /.overlay, Animagine XL 3.1 is an update in the Animagine XL V3 series, enhancing the previous version, Animagine XL 3.0. This open-source, anime-themed text-to-image model has been improved for generating anime-style images with higher quality. It includes a broader range of characters from well-known anime series, an optimized dataset, and new aesthetic tags for better image creation. Built on Stable Diffusion XL, Animagine XL 3.1…
Open weights
openrail++
2.6B parameters
diffusers
Stable Diffusion 3.5 Medium is a Multimodal Diffusion Transformer with improvements (MMDiT-X) text-to-image model that features improved performance in image quality, typography, complex prompt understanding, and resource-efficiency. Please note: This model is released under the Stability Community License. Visit Stability AI to learn or contact us for commercial licensing details. (https://arxiv.org/abs/2403.03206) with improvements that use three fixed, pretrained text encoders, with QK-normalization to improve training stability, and dual attention blocks in the first 12 transformer layers. - For individuals and organizations with annual revenue above $1M: please contact us to get an…
Access requested at publisher
other
2.5B parameters
diffusers
Distilled from Dreamshaper v7 fine-tune of Stable-Diffusion v1-5 with only 4,000 training iterations (~32 A100 GPU Hours). By distilling classifier-free guidance into the model's input, LCM can generate high-quality images in very short inference time. We compare the inference time at the setting of 768 x 768 resolution, CFG scale w=8, batchsize=4, using a A800 GPU. You can try out Latency Consistency Models directly on: To run the model yourself, you can leverage the Diffusers library: 1. Install the library: 2. Run the model: For more information, please have a look at the official docs: https://huggingface.co/docs/diffusers/api/pipelines/latentconsistencymodels#latent-consistency-models…
Open weights
mit
860M parameters
diffusers
This is an image generation model based on training from Illustrious-xl. It utilizes the latest full Danbooru and e621 datasets for training, with native tags caption. For quality tags, we evaluated image popularity through the following process: - Data normalization based on various sources and ratings. - Application of time-based decay coefficients according to date recency. - Ranking of images within the entire dataset based on this processing. Our ultimate goal is to ensure that quality tags effectively track user preferences in recent years. - Latest Danbooru images up to the training date(for v1.0,it mean approximately before 2024-10-23) - E621 images e621-2024-webp-4Mpixel dataset on…
Open weights
other
2.6B parameters
diffusers
Stable Diffusion 3.5 Large is a Multimodal Diffusion Transformer (MMDiT) text-to-image model that features improved performance in image quality, typography, complex prompt understanding, and resource-efficiency. Please note: This model is released under the Stability Community License. Visit Stability AI to learn or contact us for commercial licensing details. - For individuals and organizations with annual revenue above $1M: please contact us to get an Enterprise License. For local or self-hosted use, we recommend ComfyUI for node-based UI inference, or diffusers or GitHub for programmatic use. - Text Encoders： This model was trained on a wide variety of data, including synthetic data and…
Access requested at publisher
other
8.1B parameters
diffusers
thanks feiyuuu for report the problem. When using the default pose line the performance may be unstable, this is because the pose label use more thick line in training to have a better look. This difference can be fix by using the following method: Find the util.py in controlnetaux python package, usually the path is like: /your anaconda3 path/envs/your env name/lib/python3.8/site-packages/controlnetaux/openpose/util.py Replace the drawbodypose function with the following code: Use the code below to get started with the model. HumanArt [https://github.com/IDEA-Research/HumanArt], select 2000 images with ground truth pose annotations to generate images and calculate mAP. We are the SOTA…
Open weights
apache-2.0
1.3B parameters
diffusers
basemodel: stabilityai/stable-diffusion-xl-base-1.0 - stable-diffusion-xl - stable-diffusion-xl-diffusers - text-to-image - diffusers - inpainting SD-XL Inpainting 0.1 is a latent text-to-image diffusion model capable of generating photo-realistic images given any text input, with the extra capability of inpainting the pictures by using a mask. The SD-XL Inpainting 0.1 was initialized with the stable-diffusion-xl-base-1.0 weights. The model is trained for 40k steps at resolution 1024x1024 and 5% dropping of the text-conditioning to improve classifier-free classifier-free guidance sampling. For inpainting, the UNet has 5 additional input channels (4 for the encoded masked-image and 1 for the…
Open weights
openrail++
2.6B parameters
diffusers
/ Title Base Styling / rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.8.2/css/all.min.css" Illustrious XL is the Illustration focused Stable Diffusion XL model which is continued from Kohaku XL Beta 5, trained by OnomaAI Research Team. The model focuses on utilizing large-scale annotated dataset, Danbooru2023. We release the v0.1 and v0.1-GUIDED model here, under fair public ai license, however discourages the usage of model over monetization purpose / any closed source purposes. For full technical details, please refer to our technical report. We plan to release several aesthetic-finetuned model variants in near future. By using this model, users agree to…
Open weights
other
2.6B parameters
diffusers
The SDXL ecosystem is the single most mature corner of open image generation, and v9 is its most refined photorealism checkpoint. Choose Juggernaut XL v9 when you want: - Photorealism that holds up under scrutiny — skin texture, micro-contrast, and natural lighting that translates from concept to print. - Reasonable hardware — runs comfortably on 8 GB of VRAM, unlike newer DiT-based models that demand 16+ GB. - The full SDXL toolbox — drop-in compatibility with the thousands of SDXL ControlNets, IP-Adapter variants, AnimateDiff, regional prompting tools, and LoRAs already in your workflow. - Battle-tested reliability — 26+ months in production, used in agencies, studios, and shipping…
Open weights
creativeml-openrail-m
diffusers
Please refer to Qwen-Image-Lightning github to learn how to use the models. make sure to install diffusers from main (pip install git+https://github.com/huggingface/diffusers.git)
Open weights
apache-2.0
diffusers
Model · Text to image
nphSi
+ Always use full LoRa name with "vrtlxxxx" trigger in prompt like "Alba Baptista (vrtlalbabaptista) in a swimming pool". "Woman" or "1girl" will NOT work due to my way i do captions. + Add the gender to the prompt for confusing names like "Alex Jones". + Remove the name when internal model knowledge is bad or censored or is confusing to model like "Sandy Cheeks" or "Kate Middleton". + When using a Lora with multiple triggers (vrtlxx,vrtlyy) do not use the real character name but only trigger or a combination of it. "vrtlMain" always combines all trigger-words. Angourie Rice, January Jones, Julianna Guill, Ursula Corbero, Judith Rakers, Alina Merkau, Kiernan Shipka, Leslie Bibb, Marie…
Open weights
apache-2.0
diffusers
Recommend smthemex/ComfyUIUniBlockSwap plugin for LOW VRAM users, it only requires 4-6GB of VRAM to run the full bf16 model. 您可以尝试一下全新的 ComfyUI GGUF 模型加载插件 smthemex/ComfyUIDifGGUF，它能适配更多的 GGUF 文件格式，并且将很快集成低显存(4-8GB)显卡的 GGUF 模型块卸载管理能力。 Recommend to try the new GGUF ComfyUI loader plugin, smthemex/ComfyUIDifGGUF, it compatible with more GGUF format, and will add low VRAM (4-8GB) management for GGUF soon. 1. 图像的真实感和质感进一步改善，基本接近香蕉(Nano Banana)的水平。 2. 提示词遵循和还原能力，参数适配性和LoRA兼容性进一步改善，。 The V2 version of this model has undergone a full fine-tuning based on FLUX.2-Klein-9B-True-V1. Compared to the V1 version, it has some improvements and enhancements as below: 1. The realism and texture of images…
Open weights
other
diffusers
Welcome to the official repository for the Z-Image（造相）project! Z-Image is a powerful and highly efficient image generation model with 6B parameters. Currently there are three variants: - Z-Image-Turbo – A distilled version of Z-Image that matches or exceeds leading competitors with only 8 NFEs (Number of Function Evaluations). It offers sub-second inference latency on enterprise-grade H800 GPUs and fits comfortably within 16G VRAM consumer devices. It excels in photorealistic image generation, bilingual text rendering (English & Chinese), and robust instruction adherence. - Z-Image-Base – The non-distilled foundation model. By releasing this checkpoint, we aim to unlock the full potential…
Open weights
apache-2.0
ggml
Model · Text to image
City
This is a direct GGUF conversion of black-forest-labs/FLUX.1-dev As this is a quantized model not a finetune, all the same restrictions/original license terms still apply. The model files can be used with the ComfyUI-GGUF custom node. Place model files in ComfyUI/models/unet - see the GitHub readme for further install instructions. Please refer to this chart for a basic overview of quantization types.
Open weights
other
gguf
Pony Diffusion V6 is a versatile SDXL finetune capable of producing stunning SFW and NSFW visuals of various anthro, feral, or humanoids species and their interactions based on simple natural language prompts. CHECK "ABOUT THIS VERSION" ON THE RIGHT IF YOU ARE NOT ON "V6" FOR IMPORTANT INFORMATION. Please join our Discord Server to support development of new versions of this model and get access to free SD bot and check out more examples of this model capabilities on our prompt sharing website or follow the author on Twitter. Important information Make sure you load this model with clip skip 2 (or -2 in some software), otherwise you will be getting low quality blobs. This model supports a…
Open weights
cdla-permissive-2.0
diffusers
Get API key from ModelsLab, No Payment needed. Replace Key in below code, change modelid to "revanimated" Coding in PHP/Node/Java etc? Have a look at docs for more code examples: View docs import requests import json url = "https://stablediffusionapi.com/api/v3/dreambooth" payload = json.dumps({ "key": "", "modelid": "revanimated", "prompt": "actual 8K portrait photo of gareth person, portrait, happy colors, bright eyes, clear eyes, warm smile, smooth soft skin, big dreamy eyes, beautiful intricate colored hair, symmetrical, anime wide eyes, soft lighting, detailed face, by makoto shinkai, stanley artgerm lau, wlop, rossdraws, concept art, digital painting, looking into camera"…
Open weights
creativeml-openrail-m
diffusers
Model · Text to image
City
This is a direct GGUF conversion of black-forest-labs/FLUX.1-schnell The model files can be used with the ComfyUI-GGUF custom node. Place model files in ComfyUI/models/unet - see the GitHub readme for further install instructions. Please refer to this chart for a basic overview of quantization types.
Open weights
apache-2.0
gguf
This is a GGUF quantized version of Qwen-Image-2512. unsloth/Qwen-Image-2512-GGUF uses Unsloth Dynamic 2.0 methodology for SOTA performance. - Important layers are upcasted to higher precision. - To use the model, read our guides for ComfyUI or stable-diffusion.cpp. - Uses tooling from ComfyUI-GGUF by city96. We are excited to introduce Qwen-Image-2512, the December update of Qwen-Image’s text-to-image foundational model. You are welcome to try the latest model at Qwen Chat. Compared to the base Qwen-Image model released in August, Qwen-Image-2512 features the following key improvements: Enhanced Huamn Realism Qwen-Image-2512 significantly reduces the “AI-generated” look and substantially…
Open weights
apache-2.0
An experimental version of IP-Adapter-FaceID: we use face ID embedding from a face recognition model instead of CLIP image embedding, additionally, we use LoRA to improve ID consistency. IP-Adapter-FaceID can generate various style images conditioned on a face with only text prompts. IP-Adapter-FaceID-Plus: face ID embedding (for face ID) + CLIP image embedding (for face structure) IP-Adapter-FaceID-PlusV2: face ID embedding (for face ID) + controllable CLIP image embedding (for face structure) You can adjust the weight of the face structure to get different generation! IP-Adapter-FaceID-Portrait: same with IP-Adapter-FaceID but for portrait generation (no lora! no controlnet!).…
Open weights
diffusers
Model · Text to image
Lykon
Read more about this model here: https://civitai.com/models/4384/dreamshaper Also please support by giving 5 stars and a heart, which will notify new updates. Please consider supporting me on Patreon or buy me a coffee - https://www.patreon.com/Lykon275 - https://snipfeed.co/lykon You can run this model on: - https://huggingface.co/spaces/Lykon/DreamShaper-webui - Mage.space, sinkin.ai and more
Open weights
other
diffusers
This model suite supports two mainstream usage frameworks, with detailed guides provided below: For full documentation on model usage within the Qwen-Image-Lightning ecosystem (including environment setup, inference pipelines, and customization), please refer to: Qwen-Image-Lightning GitHub Repository The models are fully compatible with the LightX2V lightweight video/image generation inference framework. For step-by-step usage examples, configuration templates, and performance optimization tips, see: LightX2V Qwen Image Documentation
Open weights
apache-2.0
diffusers
Original model is here. This model created by Crody.
Open weights
other
2.6B parameters
diffusers
I. Introduction NetaYume Lumina is a text-to-image model fine-tuned from Neta Lumina, a high-quality anime-style image generation model developed by Neta.art Lab. It builds upon Lumina-Image-2.0, an open-source base model released by the Alpha-VLLM team at Shanghai AI Laboratory. This model was trained with the goal of not only generating realistic human images but also producing high-quality anime-style images. Despite being fine-tuned on a specific dataset, it retains a significant amount of knowledge from the base model. The file NetaYumeLuminav2allinone.safetensors is an all-in-one file that contains the necessary weights for the VAE, text encoder, and image backbone to be used with…
Open weights
apache-2.0
diffusion-single-file
Modifications to the original model card are in red or green Stable Diffusion Inpainting is a latent text-to-image diffusion model capable of generating photo-realistic images given any text input, with the extra capability of inpainting the pictures by using a mask. The Stable-Diffusion-Inpainting was initialized with the weights of the Stable-Diffusion-v-1-2. First 595k steps regular training, then 440k steps of inpainting training at resolution 512x512 on “laion-aesthetics v2 5+” and 10% dropping of the text-conditioning to improve classifier-free classifier-free guidance sampling. For inpainting, the UNet has 5 additional input channels (4 for the encoded masked-image and 1 for the mask…
Open weights
creativeml-openrail-m
diffusers
Use bucket training like novelai, can generate high resolutions images of any aspect ratio - Use large amount of high quality data(over 10000000 images), the dataset covers a diversity of situation - Use re-captioned prompt like DALLE.3, use CogVLM to generate detailed description, good prompt following ability - Use many useful tricks during training. Including but not limited to date augmentation, mutiple loss, multi resolution - Use almost the same parameter compared with original ControlNet. No obvious increase in network parameter or computation. - Support 10+ control conditions, no obvious performance drop on any single condition compared with training independently - Support multi…
Open weights
apache-2.0
1.3B parameters
diffusers
+ Always use full LoRa name with "vrtlxxxx" trigger in prompt like "Alba Baptista (vrtlalbabaptista) in a swimming pool". "Woman" or "1girl" will NOT work due to my way i do captions. + Add the gender to the prompt for confusing names like "Alex Jones". + Remove the name when internal model knowledge is bad or censored or is confusing to model like "Sandy Cheeks" or "Kate Middleton". + When using a Lora with multiple triggers (vrtlxx,vrtlyy) do not use the real character name but only trigger or a combination of it. "vrtlMain" always combines all trigger-words. Angourie Rice, January Jones, Julianna Guill, Ursula Corbero, Judith Rakers, Alina Merkau, Kiernan Shipka, Leslie Bibb, Marie…
Open weights
apache-2.0
diffusers
Model · Text to image
Lykon
lykon/dreamshaper-8 is a Stable Diffusion model that has been fine-tuned on runwayml/stable-diffusion-v1-5. For more general information on how to run text-to-image models with Diffusers, see the docs. - Version 8 focuses on improving what V7 started. Might be harder to do photorealism compared to realism focused models, as it might be hard to do anime compared to anime focused models, but it can do both pretty well if you're skilled enough. Check the examples! - Version 7 improves lora support, NSFW and realism. If you're interested in "absolute" realism, try AbsoluteReality. - Version 6 adds more lora support and more style in general. It should also be better at generating directly at…
Open weights
creativeml-openrail-m
860M parameters
diffusers
Original model is here. This model created by maxfeifei8.
Open weights
other
2.6B parameters
diffusers
Latent Consistency Model (LCM) LoRA was proposed in LCM-LoRA: A universal Stable-Diffusion Acceleration Module by Simian Luo, Yiqin Tan, Suraj Patil, Daniel Gu et al. It is a distilled consistency adapter for runwayml/stable-diffusion-v1-5 that allows to reduce the number of inference steps to only between 2 - 8 steps. LCM-LoRA is supported in Hugging Face Diffusers library from version v0.23.0 onwards. To run the model, first install the latest version of the Diffusers library as well as peft, accelerate and transformers. audio dataset from the Hugging Face Hub: Note: For detailed usage examples we recommend you to check out our official LCM-LoRA docs The adapter can be loaded with SDv1-5…
Open weights
openrail++
diffusers
Original model is here. This model created by Ikena.
Open weights
other
2.6B parameters
diffusers
This is a quantization of Tongyi-MAI/Z-Image-Turbo to FP8 E5M2 and FP8 E4M3FN. This model strictly follows the original licensing terms and usage restrictions. Please refer to the original model card for details.
Open weights
apache-2.0
diffusers
Original model is here. This model created by janxd.
Open weights
other
2.6B parameters
diffusers
SDXL-Lightning is a lightning-fast text-to-image generation model. It can generate high-quality 1024px images in a few steps. For more information, please refer to our research paper: SDXL-Lightning: Progressive Adversarial Diffusion Distillation. We open-source the model as part of the research. Our models are distilled from stabilityai/stable-diffusion-xl-base-1.0. This repository contains checkpoints for 1-step, 2-step, 4-step, and 8-step distilled models. The generation quality of our 2-step, 4-step, and 8-step model is amazing. Our 1-step model is more experimental. We provide both full UNet and LoRA checkpoints. The full UNet models have the best quality while the LoRA models can be…
Open weights
openrail++
diffusers
Original model is here. This model created by DivingSuit.
Open weights
other
2.6B parameters
diffusers
These LoRAs were extracted from fine-tuned checkpoints. I did this primarily for myself because LoRAs are easier to work with: they can be mixed in real time and assigned different weights/strengths. This also saves space on your local computer. They work well at 100–150% strength. Choose a rank according to your taste and your hardware capabilities (the lower the rank, the less memory you need). However, some of my test generations showed that a lower rank can sometimes be preferable: it does not cause artifacts, and the result is closer to the reference image generated using the checkpoint from which the LoRA was extracted. A lot of time, electricity, and compute went into this on my…
Open weights
diffusers
Model · Text to image
Alper
This repository provides an optimized FP8 (float8e4m3fn) weight-only quantized version of the newly released Krea 2 OSS (Turbo) transformer. This optimization reduces the model size from the original 24.76 GiB (BF16) down to 12.01 GiB, making it highly accessible and runnable on standard consumer hardware (such as 16GB and 24GB GPUs) without sacrificing output quality. Unlike generic global quantization scripts that aggressively convert every parameter (which often degrades generation details or introduces NaN/promotion calculation errors in neural networks), this model was quantized using a selective weight-only strategy: 1. Targeted Quantization: Only 2D floating-point weight matrices…
Open weights
other
diffusers
This repository contains Nunchaku-quantized versions of Qwen-Image-Edit, an image-editing model based on Qwen-Image, advances in complex text rendering. It is optimized for efficient inference while maintaining minimal loss in performance. No recent news. Stay tuned for updates! Data Type: INT4 for non-Blackwell GPUs (pre-50-series), NVFP4 for Blackwell GPUs (50-series). Rank: r32 for faster inference, r128 for better quality but slower inference. Standard inference speed models for general use 4-step distilled models fused with Qwen-Image-Edit-Lightning-4steps-V1.0 LoRA using LoRA strength = 1.0 8-step distilled models fused with Qwen-Image-Edit-Lightning-8steps-V1.0 LoRA using LoRA…
Open weights
apache-2.0
diffusers
HuggingFace mirror of https://civitai.com/models/1307155 You should use nsfwsks to trigger the image generation. Download them in the Files & versions tab.
Open weights
diffusers
4-bit quantized weights of [FLUX.2 [klein] 4B](https://huggingface.co/black-forest-labs/FLUX.2-klein-4B) by Black Forest Labs, optimized for mflux on Apple Silicon. FLUX.2 [klein] 4B is a 4 billion parameter rectified flow transformer by Black Forest Labs for fast image generation and editing. It delivers state-of-the-art quality with sub-second inference on consumer hardware. - Apache 2.0 — fully open for commercial use Apache 2.0, inherited from the original model.
Open weights
apache-2.0
mflux
Model · Text to image
KREA
This is the Krea 2 Raw checkpoint, its not recommended for inference use. Its a good base for finetuning or post-training for your own needs and domains. For example, one use-case is to train LoRAs on midtrain and directly use them on Krea 2 Turbo. See our collection of in-house trained LoRAs trained on Raw and meant to be used with Turbo: Krea-2 LoRA Collection 1. Setup the official Krea 2 codebase 2. Download raw.safetensors in this repo 3. export OSSRAW= Install diffusers from source (for Krea2Pipeline): Install SGLang from source (https://github.com/sgl-project/sglang) See the full SGLang Krea 2 Cookbook here This model card covers the Krea 2 model family, including the following…
Access requested at publisher
other
12.8B parameters
diffusers
用于测试基于krea2raw int8训练的人物 LoKR / LoRA，仅代表个人审美与训练效果。实际生成结果仅供测试，请勿用于冒充、欺骗或其他不当用途。 理论上在krea2 raw模型与krea2 turbo模型上均可使用，使用强度在0.8~1.5之间，高于2.0面部会开始出现明显变形； （训练方案经过一段时间的测试，仍然采用了全秩lokr，泛化、细节、相似度三者相对均衡，在训练素材质量不高的情况下也更加有效） （存疑，某些中文概念确实可以准确理解，但也不要因此对krea2的中文理解能力抱有过高的期待，目前只能说比之前的flux系列有较大进步，实际效果有待商榷，比如flux系列的老问题——krea2仍然会把中文的"桃子"大概率画成苹果） krea2 turbo fp8； euler + beta|beta57； cfg=1； lora权重1.0； 无其他lora参与。 本系列lora训练中同样添加了人物本名作为触发词，生图时需输入触发词才能准确画出对应人物（名字本身就是触发词，无需其他前缀后缀）； 触发词一般为中文，部分人物将使用英文触发词，英文触发词会包含在示例图的水印中（水印通常以girlslikekrea2 for xxx形式出现，xxx即为触发词），有水印的示例图就代表需要使用英文触发词（因为krea2目前仍然无法准确生成中文，所以水印无法使用中文来表示触发词）； 示例图片一如既往包含工作流与提示词，lora强度为1.0，均由krea2turbo fp8模型生成； 示例图人名缩写可在 girlslikeloragalleryapp…
Open weights
apache-2.0
diffusers
用于测试基于 Z-Image Base/Turbo BF16 训练的人物 LoKR / LoRA，仅代表个人审美与训练效果。实际生成结果仅供测试，请勿用于冒充、欺骗或其他不当用途。 后缀为zi代表基于z-image base训练，zit则代表基于turbo训练，zi在base与turbo模型中均可使用，zit则只能在turbo中使用。 z-image base训练尚无较为通用的可行方案，目前本zi系列选择的方案是全秩lokr，可在与turbo模型配合使用时以权重1.0出图，也能适当增加权重以增强相似性，最好不要超过1.5。 而在与base模型或相关微调模型配合使用时，可适当降低权重。 基于base训练的zi lokr在turbo模型中使用时，质感会更接近turbo本身（应该是base模型本身低噪部分难以被"污染"的缘故），中远景图中的人物相似度也会比zit好一些，近景则更"平淡"。 但总体来说兼容性存疑，比如解剖学问题仍然大量存在（在base模型上生图就存在类似问题，也影响到了训练，会让肢体问题重新变得不稳定又棘手），其他类似的问题都还在测试中，后续有更好的方案会继续更新。 z-image turbo bf16； ersde + sgmuniform | euler + flowmatch； cfg=1； lora权重0.5~1.5； 无其他lora参与。 鉴于z-image…
Open weights
apache-2.0
diffusers
An Anima fine-tune by silvermoong, using the "Evolved" training strategy with a focus on stable hands, a neutral art style that works with artist tags, and multiple characters. Update ComfyUI or Forge Neo to the latest version and restart before loading either 2.9B model. Older versions may not load or run the model correctly. Each checkpoint is a 5.84 GB BF16 diffusion model. Both use the same separate text encoder and VAE listed below. SHA-256 checksums are in releases.json. Recommended settings for standard and Turbo versions, including 2.9B, are listed below. See the Civitai release page for sample images. These are BF16 diffusion-model checkpoints. The text encoder and VAE are separate…
Open weights
other
diffusion-single-file
LoRA Flux.1-dev pour le personnage Emma Vaganova, entraînée avec le token 3mm@. Téléchargement: onglet Files and versions de ce dépôt. Utiliser 3mm@ dans le prompt (souvent en fin de phrase: Style of 3mm@). - Résolution: 896×1024 ou buckets proches (aligné sur l’entraînement multi-résolution). Les dossiers d’état d’entraînement (-state/) ne sont pas publiés ici pour l’instant: reprise Comfy = usage local uniquement. Personnage fictif inspiré de références photo; usage responsable et conforme aux conditions FLUX / OpenRAIL. Voir MODELCARD.md (steps, reprise, hyperparamètres, SHA256, limites connues).
Open weights
openrail
diffusers
H
Model · Text to image
Hub
This repository provides rh-hf-e2e-t2-20260918104741-lora weight files. You can load them on RunningHub. Published by RunningHub on behalf of the author. Copyright remains with the author. Follow the original project or upstream license. RunningHub API: RunningHub API provides unified access to 500+ AI models, including Seedance and other state-of-the-art multimodal models, at prices as low as 30% of official rates. Built for AIGC startups, AI short-form drama studios, and other production teams looking to create at scale https://www.runninghub.ai/call-api - RunningHub：https://www.runninghub.ai - RunningHub 中国站：https://www.runninghub.cn - RunningHub API…
Open weights
H
Model · Text to image
Hub
This repository provides rh-hf-e2e-t4-20260918105654-lora weight files. You can load them on RunningHub. Published by RunningHub on behalf of the author. Copyright remains with the author. Follow the original project or upstream license. RunningHub API: RunningHub API provides unified access to 500+ AI models, including Seedance and other state-of-the-art multimodal models, at prices as low as 30% of official rates. Built for AIGC startups, AI short-form drama studios, and other production teams looking to create at scale https://www.runninghub.ai/call-api - RunningHub：https://www.runninghub.ai - RunningHub 中国站：https://www.runninghub.cn - RunningHub API…
Open weights
