fal/Qwen-Image-Edit-2511-Multiple-Angles-LoRA
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Post
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(https://github.com/obsxrver/wan22-lora-training)
If youāve been wanting to train your own Wan 2.2 Video LoRAs but are intimidated by the hardware requirements, parameter tweaking insanity, or the installation nightmareāI built a solution that handles it all for you.
This is currentlyĀ the easiest, fastest, and cheapest way to get a high-quality training runĀ done.
Why this method?
* Zero Setup:Ā NoĀ installing Python, CUDA, or hunting for dependencies. You launch a pre-builtĀ [Vast.AI](http://Vast.AI) template, and it's ready in minutes.
* Full WebUI:Ā Drag-and-drop your videos/images, editĀ captions, and click "Start." No terminal commands required.
* Extremely Cheap:Ā You can rent a dual RTX 5090 node, train a full LoRA in 2-3 hours, and auto-shutdown.Ā Total cost is usually $3 or less.
* Auto-Save:Ā It automatically uploads your finished LoRA to your Cloud Storage (Google Drive/S3/Dropbox) and kills the instance so you don't pay for a second longerĀ than necessary.
How it works:
1. Click the Vast.AIĀ template link (in the repo).
2. Open the WebUI inĀ your browser.
3. Upload your dataset and press Train.
4. Come back in an hour to find your LoRA in your Google Drive.
ItĀ supports both Text-to-Video and Image-to-Video, and optimizesĀ for dual-GPU setups (training High/Low noise simultaneously) to cut training time in half.
Repo + Template Link:
https://github.com/obsxrver/wan22-lora-training
Let me know
if you have questions
If youāve been wanting to train your own Wan 2.2 Video LoRAs but are intimidated by the hardware requirements, parameter tweaking insanity, or the installation nightmareāI built a solution that handles it all for you.
This is currentlyĀ the easiest, fastest, and cheapest way to get a high-quality training runĀ done.
Why this method?
* Zero Setup:Ā NoĀ installing Python, CUDA, or hunting for dependencies. You launch a pre-builtĀ [Vast.AI](http://Vast.AI) template, and it's ready in minutes.
* Full WebUI:Ā Drag-and-drop your videos/images, editĀ captions, and click "Start." No terminal commands required.
* Extremely Cheap:Ā You can rent a dual RTX 5090 node, train a full LoRA in 2-3 hours, and auto-shutdown.Ā Total cost is usually $3 or less.
* Auto-Save:Ā It automatically uploads your finished LoRA to your Cloud Storage (Google Drive/S3/Dropbox) and kills the instance so you don't pay for a second longerĀ than necessary.
How it works:
1. Click the Vast.AIĀ template link (in the repo).
2. Open the WebUI inĀ your browser.
3. Upload your dataset and press Train.
4. Come back in an hour to find your LoRA in your Google Drive.
ItĀ supports both Text-to-Video and Image-to-Video, and optimizesĀ for dual-GPU setups (training High/Low noise simultaneously) to cut training time in half.
Repo + Template Link:
https://github.com/obsxrver/wan22-lora-training
Let me know
if you have questions
- 13 replies
liked 5 Spaces 3 months ago
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Post
3173
RTX 5090 Tested Against FLUX DEV, SD 3.5 Large, SD 3.5 Medium, SDXL, SD 1.5 with AMD 9950X CPU and RTX 5090 compared against RTX 3090 TI in all benchmarks. Moreover, compared FP8 vs FP16 and changing prompt impact as well
Video Link : https://youtu.be/jHlGzaDLkto
In this video I have intensively compared RTX 5090 speed on FLUX DEV, FLUX Fill, SD 3.5 Large, SD 3.5 Medium, Stable Diffusion XL (SDXL) and Stable Diffusion 1.5 (SD 1.5) models. For each benchmark, I have compared RTX 5090 against RTX 3090 TI so we see the speed improvement. Moreover, I have tested FP8 vs 16-bit precision for FLUX and SD 3.5 Large and SD 3.5 Medium models. Furthermore, I have tested the speed impact of changing prompt on FLUX DEV model since one of the follower had requested. Full specs of the system provided below.
I have used SwarmUI with ComfyUI backend so these benchmarks are literally done on ComfyUI you can think as. Currently no other interface / UI supporting RTX 5000 series as far as i know.
Video Link : https://youtu.be/jHlGzaDLkto
šAutomatic Installer and Model Downloader RTX 5000 Series Support ā¤µļø
ā¶ļø https://www.patreon.com/posts/installer-and-downloader-rtx5000-series-support-114517862
šManually Install RTX 5000 Series Support ā¤µļø
ā¶ļø https://github.com/comfyanonymous/ComfyUI/discussions/6643
šSECourses 10000+ Members Discord ā¤µļø
ā¶ļø https://discord.com/servers/software-engineering-courses-secourses-772774097734074388
šSECourses Amazing Generative AI GitHub ā¤µļø
ā¶ļø https://github.com/FurkanGozukara/Stable-Diffusion
šSECourses AI APPs Index ā¤µļø
ā¶ļø https://github.com/FurkanGozukara/Stable-Diffusion/blob/main/Patreon-Posts-Index.md
šGPU Specs and the used Machine Tutorial ā¤µļø
ā¶ļø https://youtu.be/uV3oqdILOmA
šRTX 5090 Benchmarking Video Series Playlist ā¤µļø
ā¶ļø https://www.youtube.com/playlist?list=PL_pbwdIyffslNd9aLizjQtHVHAMA6tpfT
Video has full chapters so please look at the video description
Video Link : https://youtu.be/jHlGzaDLkto
In this video I have intensively compared RTX 5090 speed on FLUX DEV, FLUX Fill, SD 3.5 Large, SD 3.5 Medium, Stable Diffusion XL (SDXL) and Stable Diffusion 1.5 (SD 1.5) models. For each benchmark, I have compared RTX 5090 against RTX 3090 TI so we see the speed improvement. Moreover, I have tested FP8 vs 16-bit precision for FLUX and SD 3.5 Large and SD 3.5 Medium models. Furthermore, I have tested the speed impact of changing prompt on FLUX DEV model since one of the follower had requested. Full specs of the system provided below.
I have used SwarmUI with ComfyUI backend so these benchmarks are literally done on ComfyUI you can think as. Currently no other interface / UI supporting RTX 5000 series as far as i know.
Video Link : https://youtu.be/jHlGzaDLkto
šAutomatic Installer and Model Downloader RTX 5000 Series Support ā¤µļø
ā¶ļø https://www.patreon.com/posts/installer-and-downloader-rtx5000-series-support-114517862
šManually Install RTX 5000 Series Support ā¤µļø
ā¶ļø https://github.com/comfyanonymous/ComfyUI/discussions/6643
šSECourses 10000+ Members Discord ā¤µļø
ā¶ļø https://discord.com/servers/software-engineering-courses-secourses-772774097734074388
šSECourses Amazing Generative AI GitHub ā¤µļø
ā¶ļø https://github.com/FurkanGozukara/Stable-Diffusion
šSECourses AI APPs Index ā¤µļø
ā¶ļø https://github.com/FurkanGozukara/Stable-Diffusion/blob/main/Patreon-Posts-Index.md
šGPU Specs and the used Machine Tutorial ā¤µļø
ā¶ļø https://youtu.be/uV3oqdILOmA
šRTX 5090 Benchmarking Video Series Playlist ā¤µļø
ā¶ļø https://www.youtube.com/playlist?list=PL_pbwdIyffslNd9aLizjQtHVHAMA6tpfT
Video has full chapters so please look at the video description
- 4 replies
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