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Quick test with SDXL Turbo, another amazing, super-fast diffusion model. It works right out of the box with diffusers unofficial demo txt2img and img2img:

Radamés Ajna

6,809 subscribers

219,854 次观看 • 2 年前 •via X (Twitter)

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SkalskiP 的头像

SkalskiP2 年前

@diffuserslib This is insane…

1LittleCoder💻 的头像

1LittleCoder💻2 年前

@diffuserslib Your demos are addicitive and inspiring!

Ankush Singal 的头像

Ankush Singal2 年前

@diffuserslib Is it faster compared to using with LCM ? Cheaper?

blender_ovo 的头像

blender_ovo2 年前

@diffuserslib super lcm！

🟢 ٴ` b0gie.eth🟣 的头像

🟢 ٴ` b0gie.eth🟣2 年前

@diffuserslib @Crypto_koH

かつお節的头像

かつお節2 年前

@osanseviero @diffuserslib cat power

JunMa 的头像

JunMa2 年前

@diffuserslib Thanks for sharing. This is super cool. Is there any way to fine-tune the model for img2img task?

bondarchukb 的头像

bondarchukb2 年前

@diffuserslib hmm, idk why but its working quite slow on my side, maybe because a lot of users are testing it?

Sylwester Mielniczuk 🔮💎 的头像

Sylwester Mielniczuk 🔮💎2 年前

@diffuserslib Trying to get the models, it's over 30G....

starwave 的头像

starwave2 年前

@diffuserslib It continues to blow my mind how things got so fast that you can just prompt and then surf through seeds and steps now at lightning speed to help find the image you're looking for rather than having to modify the prompt all the time, whole new way to explore!

相关视频

Thanks to the Latent Consistency Model (LCM), we're nearing real-time image diffusion. I've made a simple MJPEG server for generation stream using diffusers img2img pipeline. It's really fun to play with it. Can't wait for the ControlNet version. try it:

Thanks to the Latent Consistency Model (LCM), we're nearing real-time image diffusion. I've made a simple MJPEG server for generation stream using diffusers img2img pipeline. It's really fun to play with it. Can't wait for the ControlNet version. try it:

Radamés Ajna

231,889 次观看 • 2 年前

Introducing SDXL Turbo: A real-time text-to-image generation model. SDXL Turbo achieves state-of-the-art performance with a new distillation technology, enabling single-step image generation with unprecedented quality, reducing the required step count from 50 to just one. The code, research paper, and weights for non-commercial use are now available on our website. You can test SDXL Turbo on Stability AI’s image editing platform Clipdrop, with a beta demonstration of the real-time text-to-image generation capabilities. Learn more:

Introducing SDXL Turbo: A real-time text-to-image generation model. SDXL Turbo achieves state-of-the-art performance with a new distillation technology, enabling single-step image generation with unprecedented quality, reducing the required step count from 50 to just one. The code, research paper, and weights for non-commercial use are now available on our website. You can test SDXL Turbo on Stability AI’s image editing platform Clipdrop, with a beta demonstration of the real-time text-to-image generation capabilities. Learn more:

Stability AI

976,610 次观看 • 2 年前

Inpainting with Qwen Edit is like working with a magic brush amazing how well it works out of the box

Inpainting with Qwen Edit is like working with a magic brush amazing how well it works out of the box

Linoy Tsaban

14,561 次观看 • 11 个月前

This is getting interesting. In this iteration, the magnifying glass is tracked in real-time, feeding only what is seen through it to the diffusion process, revealing the invisible within a piece of clay. Real-time diffusion with Stream Diffusion + SDXL Turbo. #StableDiffusion #SDXLTurbo #StreamDiffusion #StabilityAI #Realtime

This is getting interesting. In this iteration, the magnifying glass is tracked in real-time, feeding only what is seen through it to the diffusion process, revealing the invisible within a piece of clay. Real-time diffusion with Stream Diffusion + SDXL Turbo. #StableDiffusion #SDXLTurbo #StreamDiffusion #StabilityAI #Realtime

Hugues Bruyère

26,432 次观看 • 2 年前

🚀Meet Gemini Diffusion, our first diffusion-based and super fast language model, just announced at Google I/O!🚀 Very excited to be able to share what I've been working on for the past little while with our amazing small team Google DeepMind.

🚀Meet Gemini Diffusion, our first diffusion-based and super fast language model, just announced at Google I/O!🚀 Very excited to be able to share what I've been working on for the past little while with our amazing small team Google DeepMind.

Ivana Balazevic

43,544 次观看 • 1 年前

🔥 Diffusers fast Inpaint by Alvaro Somoza Draw the mask over the subject you want to erase or change and write what you want to Inpaint it with. Create interesting art pieces with Diffusers and Gradio 😎

🔥 Diffusers fast Inpaint by Alvaro Somoza Draw the mask over the subject you want to erase or change and write what you want to Inpaint it with. Create interesting art pieces with Diffusers and Gradio 😎

Gradio

26,576 次观看 • 1 年前

Zero v0.3.0 just released! Not another chat box. An autonomous coding agent that lives in your terminal, owns the task, and ships. Voice dictation. OAuth profiles. Workspace trust gates. Model memory. You say what. It plans, edits, runs, verifies. Works fast with Grok 4.5

Zero v0.3.0 just released! Not another chat box. An autonomous coding agent that lives in your terminal, owns the task, and ships. Voice dictation. OAuth profiles. Workspace trust gates. Model memory. You say what. It plans, edits, runs, verifies. Works fast with Grok 4.5

GitLawb

16,169 次观看 • 1 个月前

MolmoAct2 kinda just works out of the box in an unseen environment and with unseen objects. I find it really crazy that I can just download a model from the internet and plug it into my robot and it can do some tasks at a limited capacity right away. this video is at 2x speed

MolmoAct2 kinda just works out of the box in an unseen environment and with unseen objects. I find it really crazy that I can just download a model from the internet and plug it into my robot and it can do some tasks at a limited capacity right away. this video is at 2x speed

atharva ☆

32,346 次观看 • 3 个月前

I spent a day at the Tutor office chatting with Josh Gruenstein on what it takes to bring rapidly deployed robotics to industrial scale. Check it out here (and catch my test drive of an in-the-works new model):

I spent a day at the Tutor office chatting with Josh Gruenstein on what it takes to bring rapidly deployed robotics to industrial scale. Check it out here (and catch my test drive of an in-the-works new model):

Rebecca Kaden

27,908 次观看 • 8 个月前

shadcn/create works out of the box with @Laravel Run laravel new, build your preset then apply it using the cli.

shadcn/create works out of the box with @Laravel Run laravel new, build your preset then apply it using the cli.

shadcn

73,062 次观看 • 5 个月前

A quick first pass at a new iteration of the realtime diffusion pipeline: physical interface → camera → realtime img2img → upscale → 3DGS through the new TripoSplat. Rough and held together with tape for now, but the whole loop runs end to end. Next: - better input and camera's pov, - splitting it across two machines to automate the hand-off, - and adding in the Tripo3D API for higher-res models... the 3D printer is just waiting for that. #diffusion #3DGS #TripoSplat

A quick first pass at a new iteration of the realtime diffusion pipeline: physical interface → camera → realtime img2img → upscale → 3DGS through the new TripoSplat. Rough and held together with tape for now, but the whole loop runs end to end. Next: - better input and camera's pov, - splitting it across two machines to automate the hand-off, - and adding in the Tripo3D API for higher-res models... the 3D printer is just waiting for that. #diffusion #3DGS #TripoSplat

Hugues Bruyère

15,526 次观看 • 2 个月前

In the past few weeks, I deep dived into an exploration revolving around the use of physical interfaces to feed and interact with a real-time img2img diffusion pipeline using Stream Diffusion and SDXL Turbo. What really captivated me is to use my hands, objects, art supplies, tools, and light to create images and scenes. 𝗣𝗵𝘆𝘀𝗶𝗰𝗮𝗹 𝗠𝗲𝗱𝗶𝗮 + 𝗧𝗼𝗼𝗹𝘀 I experimented with clay, manipulating different types and colors along with a selection of prompts. I used a magnifying glass, tracked in real-time, to focus the diffusion process on specific areas. Combining these tools created a dynamic and inspiring experience. Using magic clay to layer shapes and colors as a base for revealing landscapes and hidden worlds, and the magnifying glass to focus and reveal these details, was particularly effective. 𝗣𝗵𝘆𝘀𝗶𝗰𝗮𝗹 𝗟𝗶𝗴𝗵𝘁 I used light as my method of interaction with the img2img diffusion. This approach felt special right away. There was something magical about holding a physical light source and seeing it influence the generated visuals. I iterated on this technique with themes like Rococo architecture, flowers, Brutalist architecture, hidden worlds, and origami landscapes. 𝗜𝗻𝗸 + 𝗛𝘆𝗯𝗿𝗶𝗱 𝗙𝗼𝗿𝗺𝗮𝘁𝘀 I also used ink in milk as a means of physical interaction with the diffusion pipeline. As I drop ink into milk, shapes come alive instantly. By learning to manipulate the combination of physical and digital elements, I steered the generated output toward my areas of interest. These iterations extended beyond ink in milk to include the format in which these elements are contained: a circular plate or a triptych of small stainless steel trays. These formats provide a structured yet flexible framework to explore themes and narratives across multiple visual spaces. It's magical. Some of that last iteration has been captured in this insightful article by Fast Company: #stablediffusion #realtime #ai

In the past few weeks, I deep dived into an exploration revolving around the use of physical interfaces to feed and interact with a real-time img2img diffusion pipeline using Stream Diffusion and SDXL Turbo. What really captivated me is to use my hands, objects, art supplies, tools, and light to create images and scenes. 𝗣𝗵𝘆𝘀𝗶𝗰𝗮𝗹 𝗠𝗲𝗱𝗶𝗮 + 𝗧𝗼𝗼𝗹𝘀 I experimented with clay, manipulating different types and colors along with a selection of prompts. I used a magnifying glass, tracked in real-time, to focus the diffusion process on specific areas. Combining these tools created a dynamic and inspiring experience. Using magic clay to layer shapes and colors as a base for revealing landscapes and hidden worlds, and the magnifying glass to focus and reveal these details, was particularly effective. 𝗣𝗵𝘆𝘀𝗶𝗰𝗮𝗹 𝗟𝗶𝗴𝗵𝘁 I used light as my method of interaction with the img2img diffusion. This approach felt special right away. There was something magical about holding a physical light source and seeing it influence the generated visuals. I iterated on this technique with themes like Rococo architecture, flowers, Brutalist architecture, hidden worlds, and origami landscapes. 𝗜𝗻𝗸 + 𝗛𝘆𝗯𝗿𝗶𝗱 𝗙𝗼𝗿𝗺𝗮𝘁𝘀 I also used ink in milk as a means of physical interaction with the diffusion pipeline. As I drop ink into milk, shapes come alive instantly. By learning to manipulate the combination of physical and digital elements, I steered the generated output toward my areas of interest. These iterations extended beyond ink in milk to include the format in which these elements are contained: a circular plate or a triptych of small stainless steel trays. These formats provide a structured yet flexible framework to explore themes and narratives across multiple visual spaces. It's magical. Some of that last iteration has been captured in this insightful article by Fast Company: #stablediffusion #realtime #ai

Hugues Bruyère

86,381 次观看 • 2 年前

Here’s a small demo of an agent I built called Turbo. Turbo perceives what’s on screen and operates MacOS with the mouse and keyboard — like a human. It’s smart and it’s fast (and getting faster). Imagine Clawdbot/Openclaw with Turbo! I’ll likely open-source this, but before I do, I’m looking for someone to join me. DMs are open.

Here’s a small demo of an agent I built called Turbo. Turbo perceives what’s on screen and operates MacOS with the mouse and keyboard — like a human. It’s smart and it’s fast (and getting faster). Imagine Clawdbot/Openclaw with Turbo! I’ll likely open-source this, but before I do, I’m looking for someone to join me. DMs are open.

Allan

29,783 次观看 • 6 个月前

Large Language Diffusion with Masking (LLaDA) are here - and their generation looks so fucking dope! 🤯 True to Yann LeCun's vision, Ditch the auto-regressive bits and approximate the language distribution via Maximum Likelihood Estimation! So cool to watch the model denoise text from tokens in real time! - The team released their model checkpoints and there's a demo for you to play with it too! Try it out!🤗

Large Language Diffusion with Masking (LLaDA) are here - and their generation looks so fucking dope! 🤯 True to Yann LeCun's vision, Ditch the auto-regressive bits and approximate the language distribution via Maximum Likelihood Estimation! So cool to watch the model denoise text from tokens in real time! - The team released their model checkpoints and there's a demo for you to play with it too! Try it out!🤗

Vaibhav (VB) Srivastav

21,410 次观看 • 1 年前

New in v1.6.0 of the official Laravel VS Code Extension: Integration with VS Code's built-in test runner! Tests will now appear in the test explorer sidebar and you can run them right from the command palette. Works with both Pest and PHPUnit 👍 Shout out to Titas Gailius, knocked it outta the park 👏

New in v1.6.0 of the official Laravel VS Code Extension: Integration with VS Code's built-in test runner! Tests will now appear in the test explorer sidebar and you can run them right from the command palette. Works with both Pest and PHPUnit 👍 Shout out to Titas Gailius, knocked it outta the park 👏

Joe Tannenbaum

23,961 次观看 • 6 个月前

I got a diffusion model to run really fast, glued it to a LLM, and it blows my mind how much of the interactivity we expect from software (editing text, dragging things around, clicking on "links") just works™️ in pixel space. The future of software is bright

I got a diffusion model to run really fast, glued it to a LLM, and it blows my mind how much of the interactivity we expect from software (editing text, dragging things around, clicking on "links") just works™️ in pixel space. The future of software is bright

Zain Shah

22,455 次观看 • 1 个月前

Inception Labs just killed the transformer. They released Mercury 2, the world's first "diffusion" reasoning model. It's fast, and it uses a completely new model architecture... just watch this 11 min video to find out more:

Inception Labs just killed the transformer. They released Mercury 2, the world's first "diffusion" reasoning model. It's fast, and it uses a completely new model architecture... just watch this 11 min video to find out more:

David Ondrej

45,692 次观看 • 5 个月前

THIS IS MY 16 HDMI SPLITTER BOX (16 in and 1 OUT) and how it works with my new set up ..

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The Top Loader

11,283 次观看 • 5 个月前