File:Fine-tune Stable Diffusion with LoRA for as low as $1.webm
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Original file (WebM audio/video file, VP9/Opus, length 17 min 36 s, 1,920 × 1,080 pixels, 533 kbps overall, file size: 67.01 MB)
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English: Fine-tuning large models doesn't have to be complicated and expensive. In this tutorial, I provide a step-by-step demonstration of the fine-tuning process for a Stable Diffusion model geared towards Pokemon image generation. Utilizing a pre-existing script sourced from the Hugging Face diffusers library, the configuration is set to leverage the LoRA algorithm from the Hugging Face PEFT library. The training procedure is executed on a modest AWS GPU instance (g4dn.xlarge), optimizing cost-effectiveness through the utilization of EC2 Spot Instances, resulting in a total cost as low as $1.
⭐️⭐️⭐️ Don't forget to subscribe to be notified of future videos ⭐️⭐️⭐️ - Blog: https://huggingface.co/blog/lora - Model: https://huggingface.co/juliensimon/stable-diffusion-v1-5-pokemon-lora - Dataset: https://huggingface.co/datasets/lambdalabs/pokemon-blip-captions - Amazon EC2 G4 instances: https://aws.amazon.com/ec2/instance-types/g4/ Follow me on Medium at https://julsimon.medium.com or Substack at https://julsimon.substack.com. |
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| Source | YouTube: Fine-tune Stable Diffusion with LoRA for as low as $1 – View/save archived versions on archive.org and archive.today |
| Author | Julien Simon |
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Attribution: Julien Simon
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| Date/Time | Thumbnail | Dimensions | User | Comment | |
|---|---|---|---|---|---|
| current | 15:46, 11 September 2024 | 17 min 36 s, 1,920 × 1,080 (67.01 MB) | Prototyperspective (talk | contribs) | Imported media from https://www.youtube.com/watch?v=Zev6F0T1L3Y |
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