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This is native Qwen Image 2.1, no LoRA - move and resize objects seamlessly in an image🔥 I was planning to finetune on this task to showcase the new 🧨 diffusers LoRA support for Qwen 2.1 (go try it!), but while testing the base model I realized it's actually... show more

Linoy Tsaban

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50,619 görüntüleme • 4 gün önce •via X (Twitter)

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🚨 Qwen Image 2.1, the compact, efficient, and unified image creation model, is now officially supported in Draw Things! You need this amazing model! 🔄 Draw Things v26.0924.0 was released on the iOS / macOS App Store one hour ago. This version brings: 🔹 Added Qwen Image 2.1 support, including LoRA import. A 4-bit S version is also now available. 🔹 Added Sol Attention support to speed up MiniMax H3. 🔹 Some minor UI fixes.

🚨 Qwen Image 2.1, the compact, efficient, and unified image creation model, is now officially supported in Draw Things! You need this amazing model! 🔄 Draw Things v26.0924.0 was released on the iOS / macOS App Store one hour ago. This version brings: 🔹 Added Qwen Image 2.1 support, including LoRA import. A 4-bit S version is also now available. 🔹 Added Sol Attention support to speed up MiniMax H3. 🔹 Some minor UI fixes.

Draw Things

11,586 görüntüleme • 6 gün önce

We’re finally getting layers in AI images. The new Qwen Image Layered LoRA allows you to decompose any image into layers - which means you can move, resize, or replace an object / background. This is Photoshop-grade editing, offered as an open source model 🤯

We’re finally getting layers in AI images. The new Qwen Image Layered LoRA allows you to decompose any image into layers - which means you can move, resize, or replace an object / background. This is Photoshop-grade editing, offered as an open source model 🤯

Justine Moore

50,816 görüntüleme • 9 ay önce

Qwen just released Qwen-Image-2.1, and this is exactly why open models matter. I loaded it onto my NVIDIA DGX Spark and built Spark Image Lab, a local image generation and editing workspace designed for the DGX Spark ecosystem. QWEN-IMAGE-2.1 • Text-to-image generation • Image editing • Native transparent/RGBA workflows • Up to 10 reference images • Strong identity and product preservation • Improved typography, lighting, textures and detail SPARK IMAGE LAB • Clean Gradio interface • Width and height controls • Steps, seed and batch controls • Persistent generation history • Prompts and settings saved with every result • Reference images saved and restored • Docker setup for DGX Spark • Measured DGX Spark performance benchmarks Everything runs locally. Spark Image Lab is now open source under the MIT License. This is the first public alpha, so clone it, test it on your DGX Spark, open an issue and show me what you create. MODEL REPO

Qwen just released Qwen-Image-2.1, and this is exactly why open models matter. I loaded it onto my NVIDIA DGX Spark and built Spark Image Lab, a local image generation and editing workspace designed for the DGX Spark ecosystem. QWEN-IMAGE-2.1 • Text-to-image generation • Image editing • Native transparent/RGBA workflows • Up to 10 reference images • Strong identity and product preservation • Improved typography, lighting, textures and detail SPARK IMAGE LAB • Clean Gradio interface • Width and height controls • Steps, seed and batch controls • Persistent generation history • Prompts and settings saved with every result • Reference images saved and restored • Docker setup for DGX Spark • Measured DGX Spark performance benchmarks Everything runs locally. Spark Image Lab is now open source under the MIT License. This is the first public alpha, so clone it, test it on your DGX Spark, open an issue and show me what you create. MODEL REPO

Joey

23,578 görüntüleme • 11 gün önce

🚀 Update Next Scene V2 only 10 days after last version, now live on Hugging Face 👉 🎬 A LoRA made for Qwen Image Edit 2509 that lets you create seamless cinematic “next shots” — keeping the same characters, lighting, and mood. I trained this new version on thousands of paired cinematic shots to make scene transitions smoother, more emotional, and real. 🧠 What’s new: • Much stronger consistency across shots • Better lighting and character preservation • Smoother transitions and framing logic • No more black bar artifacts Built for storytellers using ComfyUI or any diffusers pipeline. Just use “Next Scene:” and describe what happens next , the model keeps everything coherent. 🧩 Try it directly in ComfyUI, or check the thread to launch it on fal . Open-source, no restrictions, made for filmmakers, animators, and dreamers. ComfyUI #AIcinema #LoRA #Flux #Qwen #ComfyUI #AIart #GenerativeVideo you can test on comfyui or to try on you can go here : and use my lora link : start your prompt with "Next Scene:" and lets go !!

🚀 Update Next Scene V2 only 10 days after last version, now live on Hugging Face 👉 🎬 A LoRA made for Qwen Image Edit 2509 that lets you create seamless cinematic “next shots” — keeping the same characters, lighting, and mood. I trained this new version on thousands of paired cinematic shots to make scene transitions smoother, more emotional, and real. 🧠 What’s new: • Much stronger consistency across shots • Better lighting and character preservation • Smoother transitions and framing logic • No more black bar artifacts Built for storytellers using ComfyUI or any diffusers pipeline. Just use “Next Scene:” and describe what happens next , the model keeps everything coherent. 🧩 Try it directly in ComfyUI, or check the thread to launch it on fal . Open-source, no restrictions, made for filmmakers, animators, and dreamers. ComfyUI #AIcinema #LoRA #Flux #Qwen #ComfyUI #AIart #GenerativeVideo you can test on comfyui or to try on you can go here : and use my lora link : start your prompt with "Next Scene:" and lets go !!

Lovis Odin

43,366 görüntüleme • 11 ay önce

AudioLDM is a text-to-audio model by Haohe Liu et al. It is available in the 🧨 Diffusers library from v0.15.0 onwards, and is capable of generating realistic music, sound effects and speech Try it in this Colab to generate music for yourself:

AudioLDM is a text-to-audio model by Haohe Liu et al. It is available in the 🧨 Diffusers library from v0.15.0 onwards, and is capable of generating realistic music, sound effects and speech Try it in this Colab to generate music for yourself:

Sanchit Gandhi

27,143 görüntüleme • 3 yıl önce

🧮Turn single image into a custom LoRA model in one click ! Should work for character and product ! This ComfyUI workflow: → Uses Gemini AI to generate 20 diverse prompts from your image → Creates 20 consistent variations with FLUX.1 Kontext → Automatically builds the dataset + trains the LoRA One image in → Trained LoRA out 🎯 #ComfyUI #LoRA #AIArt #FLUX #AutomatedAI ComfyUI BlackForestLabsAI - Unofficial 🔗 Check it out: This workflow was made for the hackathon organized by ComfyUI in SF yesterday

🧮Turn single image into a custom LoRA model in one click ! Should work for character and product ! This ComfyUI workflow: → Uses Gemini AI to generate 20 diverse prompts from your image → Creates 20 consistent variations with FLUX.1 Kontext → Automatically builds the dataset + trains the LoRA One image in → Trained LoRA out 🎯 #ComfyUI #LoRA #AIArt #FLUX #AutomatedAI ComfyUI BlackForestLabsAI - Unofficial 🔗 Check it out: This workflow was made for the hackathon organized by ComfyUI in SF yesterday

Lovis Odin

69,609 görüntüleme • 1 yıl önce

Okay, I am fairly confident in my hypothesis now. The secret sauce behind Qwen 3.8 27B becomes almost immediately evident during testing. It is not the training data. In fact, I doubt any SFT was involved at all. The model was simply allowed GRPO with a more liberal reasoning context length. As I have explained to you before, distillation through GRPO is powerful, and in certain contexts vastly superior to K/L divergence distillation. Qwen used the outputs of Qwen 3.8 Max as the reinforcement learning objective for Qwen 3.8 27B and told the model reason as much as it has to in order to match the output. Remember, Intelligence is solution, not compression. This is like nesting the output of a function as an additional input to itself, and it is absolutely brilliant.

Okay, I am fairly confident in my hypothesis now. The secret sauce behind Qwen 3.8 27B becomes almost immediately evident during testing. It is not the training data. In fact, I doubt any SFT was involved at all. The model was simply allowed GRPO with a more liberal reasoning context length. As I have explained to you before, distillation through GRPO is powerful, and in certain contexts vastly superior to K/L divergence distillation. Qwen used the outputs of Qwen 3.8 Max as the reinforcement learning objective for Qwen 3.8 27B and told the model reason as much as it has to in order to match the output. Remember, Intelligence is solution, not compression. This is like nesting the output of a function as an additional input to itself, and it is absolutely brilliant.

Aesther

123,124 görüntüleme • 1 ay önce

adding camera control to the list of things Qwen Image Edit is great at + with a specialized multi-angle LoRA it's even better✨ > rotate the camera > tilt between bird’s-eye and worm’s-eye views > adjust lens (wide, close-up) of course we built a demo for it 🤝📹

adding camera control to the list of things Qwen Image Edit is great at + with a specialized multi-angle LoRA it's even better✨ > rotate the camera > tilt between bird’s-eye and worm’s-eye views > adjust lens (wide, close-up) of course we built a demo for it 🤝📹

Linoy Tsaban

375,611 görüntüleme • 11 ay önce

✨ Excited to share QVQ-Max, our visual reasoning model that's still evolving We've been experimenting with this approach for a while - try it out on Qwen Chat! ( 🚀 Just upload any image or video, ask away, and hit the "Thinking" button to see how it processes visual information step-by-step. It's a work-in-progress but fascinating to watch! Your early feedback will be super helpful as we continue developing! 🙏 Blog:

✨ Excited to share QVQ-Max, our visual reasoning model that's still evolving We've been experimenting with this approach for a while - try it out on Qwen Chat! ( 🚀 Just upload any image or video, ask away, and hit the "Thinking" button to see how it processes visual information step-by-step. It's a work-in-progress but fascinating to watch! Your early feedback will be super helpful as we continue developing! 🙏 Blog:

Qwen

147,163 görüntüleme • 1 yıl önce

Okay so someone suggested trying WAN 2.1, a video model that supports LoRas So I trained a LoRa of myself and it works really really well, super high resemblance, obviously you can't use a Flux LoRa but similar effect, it just works great A few annoying things: - WAN 2.1 FPS is like 16 fps, so jittery, so you have to run it through an interpolator to add another frame to get close to 30fps - Limited to about 5 seconds clips (but that seems to be a bug, see "Bug Fix I2V Frame Count Hardcoded to 81 (!!) and Optional Batch Mode") Here it is with WAN LoRa + my ElevenLabs voice + 2x interpolation + boomerang loop to make it from 5 into a 10 second video Very big potential this is the working solution if I can make this pipeline work 🤯🤯🤯🤯🤯🤯

Okay so someone suggested trying WAN 2.1, a video model that supports LoRas So I trained a LoRa of myself and it works really really well, super high resemblance, obviously you can't use a Flux LoRa but similar effect, it just works great A few annoying things: - WAN 2.1 FPS is like 16 fps, so jittery, so you have to run it through an interpolator to add another frame to get close to 30fps - Limited to about 5 seconds clips (but that seems to be a bug, see "Bug Fix I2V Frame Count Hardcoded to 81 (!!) and Optional Batch Mode") Here it is with WAN LoRa + my ElevenLabs voice + 2x interpolation + boomerang loop to make it from 5 into a 10 second video Very big potential this is the working solution if I can make this pipeline work 🤯🤯🤯🤯🤯🤯

@levelsio

126,971 görüntüleme • 1 yıl önce

I spent my Astra tokens trying to teach small Qwen3.5 (9B) to create lowpoly 3D rooms using Blender 🏡 you (or Astra) can take this challenge today here's what I learned: > you need to align geometry with deterministic rewards and VLM-as-a-judge (GLM-5.3-Flash which was a great judge) > I tried GEPA at first with various rewards, model learned to make valid rooms (but that's it) > after solving geometry you need the model to add more details, which is very hard > the stricter the reward function, less advantage you get because task is too hard. grpo didn't help > I tried passing image guidance to both policy (Qwen) and judge (GLM) it didn't improve > I tried tastemaxxing trick in this blog, truth is, flowers can be abstract, a house can't be shoutout to OpenEnv, environment is super simple what can you try? > experiment with different rewards or policy (teach a larger Qwen) > generate a dataset of 150-200 Blender render Bpy examples using Astra, fine-tune Qwen on it first and then try GEPA or GRPO > ???

I spent my Astra tokens trying to teach small Qwen3.5 (9B) to create lowpoly 3D rooms using Blender 🏡 you (or Astra) can take this challenge today here's what I learned: > you need to align geometry with deterministic rewards and VLM-as-a-judge (GLM-5.3-Flash which was a great judge) > I tried GEPA at first with various rewards, model learned to make valid rooms (but that's it) > after solving geometry you need the model to add more details, which is very hard > the stricter the reward function, less advantage you get because task is too hard. grpo didn't help > I tried passing image guidance to both policy (Qwen) and judge (GLM) it didn't improve > I tried tastemaxxing trick in this blog, truth is, flowers can be abstract, a house can't be shoutout to OpenEnv, environment is super simple what can you try? > experiment with different rewards or policy (teach a larger Qwen) > generate a dataset of 150-200 Blender render Bpy examples using Astra, fine-tune Qwen on it first and then try GEPA or GRPO > ???

merve

22,903 görüntüleme • 24 gün önce

From product image to video with just one tool - Dzine As you may have noticed, this is one of my favorite tools. It is also very underrated, as probably 50% of my tutorials include some workflow. I was testing the new image-to-video option today, and I love it. Step - by step guide in comments 🔽 I can do 95% of a workflow without switching between apps. Image generation, Image to image with style reference, background removal, background generation, and 2 frames image to video. The only other app I have been using for this video is CapCut so that I can stitch it together. Step by step 🔽

From product image to video with just one tool - Dzine As you may have noticed, this is one of my favorite tools. It is also very underrated, as probably 50% of my tutorials include some workflow. I was testing the new image-to-video option today, and I love it. Step - by step guide in comments 🔽 I can do 95% of a workflow without switching between apps. Image generation, Image to image with style reference, background removal, background generation, and 2 frames image to video. The only other app I have been using for this video is CapCut so that I can stitch it together. Step by step 🔽

Teodora P L

28,523 görüntüleme • 2 yıl önce

🚨 Qwen new checkpoint - kieran As usual it claims he is claude and made by anthropic but with tokenizer prompt , its clear - QWEN model Ignore website this is my test to know which model is which behind the scene , should i test it and compare with kimi k3 / opus 5 /sol 5.6

🚨 Qwen new checkpoint - kieran As usual it claims he is claude and made by anthropic but with tokenizer prompt , its clear - QWEN model Ignore website this is my test to know which model is which behind the scene , should i test it and compare with kimi k3 / opus 5 /sol 5.6

Chetaslua

15,544 görüntüleme • 2 ay önce

LTX 2.3 is now live on Krea. this video model generates for 1/10th the cost of other top models and can learn any style or character - just upload some references and train a lora try it now 👇

LTX 2.3 is now live on Krea. this video model generates for 1/10th the cost of other top models and can learn any style or character - just upload some references and train a lora try it now 👇

Krea

21,845 görüntüleme • 5 ay önce

🚨 one person can now do the work of an entire creative team. i just tested it on a real one. a friend needed an ad for his brand, so I opened the new Runway Agent 2.0 to try it out. here's how it went: → it generated the music and the key image first, so I could approve the direction → once I gave the ok, it built the full video around it → and when something was off, i changed just that one piece, without redoing the rest one prompt, and I had the ad we needed, work that used to take weeks. this is what it made 👇 if you want to try it → · 30% off 3 months with code RUNWAYAGENT — made with Runway · #MadeWithRunway · #ad

brenz.

28,698 görüntüleme • 3 ay önce