huggingface · sayakpaul · Feb 22, 2025 · Feb 20, 2025 · Feb 20, 2025 · Feb 21, 2025
diff --git a/docs/source/en/api/pipelines/amused.md b/docs/source/en/api/pipelines/amused.md
@@ -12,6 +12,10 @@ specific language governing permissions and limitations under the License.
 
 # aMUSEd
 
+<div class="flex flex-wrap space-x-1">
+  <img alt="LoRA" src="https://img.shields.io/badge/LoRA-d8b4fe?style=flat"/>
+</div>
+
 aMUSEd was introduced in [aMUSEd: An Open MUSE Reproduction](https://huggingface.co/papers/2401.01808) by Suraj Patil, William Berman, Robin Rombach, and Patrick von Platen.
 
 Amused is a lightweight text to image model based off of the [MUSE](https://arxiv.org/abs/2301.00704) architecture. Amused is particularly useful in applications that require a lightweight and fast model such as generating many images quickly at once.

diff --git a/docs/source/en/api/pipelines/animatediff.md b/docs/source/en/api/pipelines/animatediff.md
@@ -12,6 +12,10 @@ specific language governing permissions and limitations under the License.
 
 # Text-to-Video Generation with AnimateDiff
 
+<div class="flex flex-wrap space-x-1">
+  <img alt="LoRA" src="https://img.shields.io/badge/LoRA-d8b4fe?style=flat"/>
+</div>
+
 ## Overview
 
 [AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning](https://arxiv.org/abs/2307.04725) by Yuwei Guo, Ceyuan Yang, Anyi Rao, Yaohui Wang, Yu Qiao, Dahua Lin, Bo Dai.

diff --git a/docs/source/en/api/pipelines/cogvideox.md b/docs/source/en/api/pipelines/cogvideox.md
@@ -15,6 +15,10 @@
 
 # CogVideoX
 
+<div class="flex flex-wrap space-x-1">
+  <img alt="LoRA" src="https://img.shields.io/badge/LoRA-d8b4fe?style=flat"/>
+</div>
+
 [CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer](https://arxiv.org/abs/2408.06072) from Tsinghua University & ZhipuAI, by Zhuoyi Yang, Jiayan Teng, Wendi Zheng, Ming Ding, Shiyu Huang, Jiazheng Xu, Yuanming Yang, Wenyi Hong, Xiaohan Zhang, Guanyu Feng, Da Yin, Xiaotao Gu, Yuxuan Zhang, Weihan Wang, Yean Cheng, Ting Liu, Bin Xu, Yuxiao Dong, Jie Tang.
 
 The abstract from the paper is:

diff --git a/docs/source/en/api/pipelines/deepfloyd_if.md b/docs/source/en/api/pipelines/deepfloyd_if.md
@@ -12,6 +12,10 @@ specific language governing permissions and limitations under the License.
 
 # DeepFloyd IF
 
+<div class="flex flex-wrap space-x-1">
+  <img alt="LoRA" src="https://img.shields.io/badge/LoRA-d8b4fe?style=flat"/>
+</div>
+
 ## Overview
 
 DeepFloyd IF is a novel state-of-the-art open-source text-to-image model with a high degree of photorealism and language understanding.

diff --git a/docs/source/en/api/pipelines/flux.md b/docs/source/en/api/pipelines/flux.md
@@ -12,6 +12,10 @@ specific language governing permissions and limitations under the License.
 
 # Flux
 
+<div class="flex flex-wrap space-x-1">
+  <img alt="LoRA" src="https://img.shields.io/badge/LoRA-d8b4fe?style=flat"/>
+</div>
+
 Flux is a series of text-to-image generation models based on diffusion transformers. To know more about Flux, check out the original [blog post](https://blackforestlabs.ai/announcing-black-forest-labs/) by the creators of Flux, Black Forest Labs.
 
 Original model checkpoints for Flux can be found [here](https://huggingface.co/black-forest-labs). Original inference code can be found [here](https://github.com/black-forest-labs/flux).

diff --git a/docs/source/en/api/pipelines/hunyuan_video.md b/docs/source/en/api/pipelines/hunyuan_video.md
@@ -14,6 +14,10 @@
 
 # HunyuanVideo
 
+<div class="flex flex-wrap space-x-1">
+  <img alt="LoRA" src="https://img.shields.io/badge/LoRA-d8b4fe?style=flat"/>
+</div>
+
 [HunyuanVideo](https://www.arxiv.org/abs/2412.03603) by Tencent.
 
 *Recent advancements in video generation have significantly impacted daily life for both individuals and industries. However, the leading video generation models remain closed-source, resulting in a notable performance gap between industry capabilities and those available to the public. In this report, we introduce HunyuanVideo, an innovative open-source video foundation model that demonstrates performance in video generation comparable to, or even surpassing, that of leading closed-source models. HunyuanVideo encompasses a comprehensive framework that integrates several key elements, including data curation, advanced architectural design, progressive model scaling and training, and an efficient infrastructure tailored for large-scale model training and inference. As a result, we successfully trained a video generative model with over 13 billion parameters, making it the largest among all open-source models. We conducted extensive experiments and implemented a series of targeted designs to ensure high visual quality, motion dynamics, text-video alignment, and advanced filming techniques. According to evaluations by professionals, HunyuanVideo outperforms previous state-of-the-art models, including Runway Gen-3, Luma 1.6, and three top-performing Chinese video generative models. By releasing the code for the foundation model and its applications, we aim to bridge the gap between closed-source and open-source communities. This initiative will empower individuals within the community to experiment with their ideas, fostering a more dynamic and vibrant video generation ecosystem. The code is publicly available at [this https URL](https://github.com/tencent/HunyuanVideo).*

diff --git a/docs/source/en/api/pipelines/kandinsky3.md b/docs/source/en/api/pipelines/kandinsky3.md
@@ -9,6 +9,10 @@ specific language governing permissions and limitations under the License.
 
 # Kandinsky 3
 
+<div class="flex flex-wrap space-x-1">
+  <img alt="LoRA" src="https://img.shields.io/badge/LoRA-d8b4fe?style=flat"/>
+</div>
+
 Kandinsky 3 is created by [Vladimir Arkhipkin](https://github.com/oriBetelgeuse),[Anastasia Maltseva](https://github.com/NastyaMittseva),[Igor Pavlov](https://github.com/boomb0om),[Andrei Filatov](https://github.com/anvilarth),[Arseniy Shakhmatov](https://github.com/cene555),[Andrey Kuznetsov](https://github.com/kuznetsoffandrey),[Denis Dimitrov](https://github.com/denndimitrov), [Zein Shaheen](https://github.com/zeinsh)
 
 The description from it's GitHub page:

diff --git a/docs/source/en/api/pipelines/kolors.md b/docs/source/en/api/pipelines/kolors.md
@@ -12,6 +12,10 @@ specific language governing permissions and limitations under the License.
 
 # Kolors: Effective Training of Diffusion Model for Photorealistic Text-to-Image Synthesis
 
+<div class="flex flex-wrap space-x-1">
+  <img alt="LoRA" src="https://img.shields.io/badge/LoRA-d8b4fe?style=flat"/>
+</div>
+
 ![](https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/kolors/kolors_header_collage.png)
 
 Kolors is a large-scale text-to-image generation model based on latent diffusion, developed by [the Kuaishou Kolors team](https://github.com/Kwai-Kolors/Kolors). Trained on billions of text-image pairs, Kolors exhibits significant advantages over both open-source and closed-source models in visual quality, complex semantic accuracy, and text rendering for both Chinese and English characters. Furthermore, Kolors supports both Chinese and English inputs, demonstrating strong performance in understanding and generating Chinese-specific content. For more details, please refer to this [technical report](https://github.com/Kwai-Kolors/Kolors/blob/master/imgs/Kolors_paper.pdf).

diff --git a/docs/source/en/api/pipelines/latent_consistency_models.md b/docs/source/en/api/pipelines/latent_consistency_models.md
@@ -12,6 +12,10 @@ specific language governing permissions and limitations under the License.
 
 # Latent Consistency Models
 
+<div class="flex flex-wrap space-x-1">
+  <img alt="LoRA" src="https://img.shields.io/badge/LoRA-d8b4fe?style=flat"/>
+</div>
+
 Latent Consistency Models (LCMs) were proposed in [Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference](https://huggingface.co/papers/2310.04378) by Simian Luo, Yiqin Tan, Longbo Huang, Jian Li, and Hang Zhao.
 
 The abstract of the paper is as follows:

diff --git a/docs/source/en/api/pipelines/ledits_pp.md b/docs/source/en/api/pipelines/ledits_pp.md
@@ -12,6 +12,10 @@ specific language governing permissions and limitations under the License.
 
 # LEDITS++
 
+<div class="flex flex-wrap space-x-1">
+  <img alt="LoRA" src="https://img.shields.io/badge/LoRA-d8b4fe?style=flat"/>
+</div>
+
 LEDITS++ was proposed in [LEDITS++: Limitless Image Editing using Text-to-Image Models](https://huggingface.co/papers/2311.16711) by Manuel Brack, Felix Friedrich, Katharina Kornmeier, Linoy Tsaban, Patrick Schramowski, Kristian Kersting, Apolinário Passos.
 
 The abstract from the paper is:

diff --git a/docs/source/en/api/pipelines/ltx_video.md b/docs/source/en/api/pipelines/ltx_video.md
@@ -14,6 +14,10 @@
 
 # LTX Video
 
+<div class="flex flex-wrap space-x-1">
+  <img alt="LoRA" src="https://img.shields.io/badge/LoRA-d8b4fe?style=flat"/>
+</div>
+
 [LTX Video](https://huggingface.co/Lightricks/LTX-Video) is the first DiT-based video generation model capable of generating high-quality videos in real-time. It produces 24 FPS videos at a 768x512 resolution faster than they can be watched. Trained on a large-scale dataset of diverse videos, the model generates high-resolution videos with realistic and varied content. We provide a model for both text-to-video as well as image + text-to-video usecases.
 
 <Tip>

diff --git a/docs/source/en/api/pipelines/lumina2.md b/docs/source/en/api/pipelines/lumina2.md
@@ -14,6 +14,10 @@
 
 # Lumina2
 
+<div class="flex flex-wrap space-x-1">
+  <img alt="LoRA" src="https://img.shields.io/badge/LoRA-d8b4fe?style=flat"/>
+</div>
+
 [Lumina Image 2.0: A Unified and Efficient Image Generative Model](https://huggingface.co/Alpha-VLLM/Lumina-Image-2.0) is a 2 billion parameter flow-based diffusion transformer capable of generating diverse images from text descriptions.
 
 The abstract from the paper is:

diff --git a/docs/source/en/api/pipelines/mochi.md b/docs/source/en/api/pipelines/mochi.md
@@ -15,6 +15,10 @@
 
 # Mochi 1 Preview
 
+<div class="flex flex-wrap space-x-1">
+  <img alt="LoRA" src="https://img.shields.io/badge/LoRA-d8b4fe?style=flat"/>
+</div>
+
 > [!TIP]
 > Only a research preview of the model weights is available at the moment.
 

diff --git a/docs/source/en/api/pipelines/pia.md b/docs/source/en/api/pipelines/pia.md
@@ -12,6 +12,10 @@ specific language governing permissions and limitations under the License.
 
 # Image-to-Video Generation with PIA (Personalized Image Animator)
 
+<div class="flex flex-wrap space-x-1">
+  <img alt="LoRA" src="https://img.shields.io/badge/LoRA-d8b4fe?style=flat"/>
+</div>
+
 ## Overview
 
 [PIA: Your Personalized Image Animator via Plug-and-Play Modules in Text-to-Image Models](https://arxiv.org/abs/2312.13964) by Yiming Zhang, Zhening Xing, Yanhong Zeng, Youqing Fang, Kai Chen

diff --git a/docs/source/en/api/pipelines/pix2pix.md b/docs/source/en/api/pipelines/pix2pix.md
@@ -12,6 +12,10 @@ specific language governing permissions and limitations under the License.
 
 # InstructPix2Pix
 
+<div class="flex flex-wrap space-x-1">
+  <img alt="LoRA" src="https://img.shields.io/badge/LoRA-d8b4fe?style=flat"/>
+</div>
+
 [InstructPix2Pix: Learning to Follow Image Editing Instructions](https://huggingface.co/papers/2211.09800) is by Tim Brooks, Aleksander Holynski and Alexei A. Efros.
 
 The abstract from the paper is:

diff --git a/docs/source/en/api/pipelines/sana.md b/docs/source/en/api/pipelines/sana.md
@@ -14,6 +14,10 @@
 
 # SanaPipeline
 
+<div class="flex flex-wrap space-x-1">
+  <img alt="LoRA" src="https://img.shields.io/badge/LoRA-d8b4fe?style=flat"/>
+</div>
+
 [SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformers](https://huggingface.co/papers/2410.10629) from NVIDIA and MIT HAN Lab, by Enze Xie, Junsong Chen, Junyu Chen, Han Cai, Haotian Tang, Yujun Lin, Zhekai Zhang, Muyang Li, Ligeng Zhu, Yao Lu, Song Han.
 
 The abstract from the paper is:

diff --git a/docs/source/en/api/pipelines/stable_diffusion/overview.md b/docs/source/en/api/pipelines/stable_diffusion/overview.md
@@ -12,6 +12,10 @@ specific language governing permissions and limitations under the License.
 
 # Stable Diffusion pipelines
 
+<div class="flex flex-wrap space-x-1">
+  <img alt="LoRA" src="https://img.shields.io/badge/LoRA-d8b4fe?style=flat"/>
+</div>
+
 Stable Diffusion is a text-to-image latent diffusion model created by the researchers and engineers from [CompVis](https://github.com/CompVis), [Stability AI](https://stability.ai/) and [LAION](https://laion.ai/). Latent diffusion applies the diffusion process over a lower dimensional latent space to reduce memory and compute complexity. This specific type of diffusion model was proposed in [High-Resolution Image Synthesis with Latent Diffusion Models](https://huggingface.co/papers/2112.10752) by Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, Björn Ommer.
 
 Stable Diffusion is trained on 512x512 images from a subset of the LAION-5B dataset. This model uses a frozen CLIP ViT-L/14 text encoder to condition the model on text prompts. With its 860M UNet and 123M text encoder, the model is relatively lightweight and can run on consumer GPUs.

diff --git a/docs/source/en/api/pipelines/stable_diffusion/stable_diffusion_3.md b/docs/source/en/api/pipelines/stable_diffusion/stable_diffusion_3.md
@@ -12,6 +12,10 @@ specific language governing permissions and limitations under the License.
 
 # Stable Diffusion 3
 
+<div class="flex flex-wrap space-x-1">
+  <img alt="LoRA" src="https://img.shields.io/badge/LoRA-d8b4fe?style=flat"/>
+</div>
+
 Stable Diffusion 3 (SD3) was proposed in [Scaling Rectified Flow Transformers for High-Resolution Image Synthesis](https://arxiv.org/pdf/2403.03206.pdf) by Patrick Esser, Sumith Kulal, Andreas Blattmann, Rahim Entezari, Jonas Muller, Harry Saini, Yam Levi, Dominik Lorenz, Axel Sauer, Frederic Boesel, Dustin Podell, Tim Dockhorn, Zion English, Kyle Lacey, Alex Goodwin, Yannik Marek, and Robin Rombach.
 
 The abstract from the paper is:

diff --git a/docs/source/en/api/pipelines/stable_diffusion/stable_diffusion_xl.md b/docs/source/en/api/pipelines/stable_diffusion/stable_diffusion_xl.md
@@ -12,6 +12,10 @@ specific language governing permissions and limitations under the License.
 
 # Stable Diffusion XL
 
+<div class="flex flex-wrap space-x-1">
+  <img alt="LoRA" src="https://img.shields.io/badge/LoRA-d8b4fe?style=flat"/>
+</div>
+
 Stable Diffusion XL (SDXL) was proposed in [SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis](https://huggingface.co/papers/2307.01952) by Dustin Podell, Zion English, Kyle Lacey, Andreas Blattmann, Tim Dockhorn, Jonas Müller, Joe Penna, and Robin Rombach.
 
 The abstract from the paper is:

diff --git a/docs/source/en/api/pipelines/text_to_video.md b/docs/source/en/api/pipelines/text_to_video.md
@@ -18,6 +18,10 @@ specific language governing permissions and limitations under the License.
 
 # Text-to-video
 
+<div class="flex flex-wrap space-x-1">
+  <img alt="LoRA" src="https://img.shields.io/badge/LoRA-d8b4fe?style=flat"/>
+</div>
+
 [ModelScope Text-to-Video Technical Report](https://arxiv.org/abs/2308.06571) is by Jiuniu Wang, Hangjie Yuan, Dayou Chen, Yingya Zhang, Xiang Wang, Shiwei Zhang.
 
 The abstract from the paper is:

diff --git a/docs/source/en/api/pipelines/unidiffuser.md b/docs/source/en/api/pipelines/unidiffuser.md
@@ -12,6 +12,10 @@ specific language governing permissions and limitations under the License.
 
 # UniDiffuser
 
+<div class="flex flex-wrap space-x-1">
+  <img alt="LoRA" src="https://img.shields.io/badge/LoRA-d8b4fe?style=flat"/>
+</div>
+
 The UniDiffuser model was proposed in [One Transformer Fits All Distributions in Multi-Modal Diffusion at Scale](https://huggingface.co/papers/2303.06555) by Fan Bao, Shen Nie, Kaiwen Xue, Chongxuan Li, Shi Pu, Yaole Wang, Gang Yue, Yue Cao, Hang Su, Jun Zhu.
 
 The abstract from the paper is:

diff --git a/docs/source/en/api/pipelines/wuerstchen.md b/docs/source/en/api/pipelines/wuerstchen.md
@@ -12,6 +12,10 @@ specific language governing permissions and limitations under the License.
 
 # Würstchen
 
+<div class="flex flex-wrap space-x-1">
+  <img alt="LoRA" src="https://img.shields.io/badge/LoRA-d8b4fe?style=flat"/>
+</div>
+
 <img src="https://github.com/dome272/Wuerstchen/assets/61938694/0617c863-165a-43ee-9303-2a17299a0cf9">
 
 [Wuerstchen: An Efficient Architecture for Large-Scale Text-to-Image Diffusion Models](https://huggingface.co/papers/2306.00637) is by Pablo Pernias, Dominic Rampas, Mats L. Richter and Christopher Pal and Marc Aubreville.