KingHsp/vram-sage-training
The 2026 VRAM-Smart Fine-Tuning Suite for SDXL and ANIMA on 12GB GPUs
- Stars
- 56
- Forks
- 0
- Open issues
- 0
- Last push
- today
About vram-sage-training
vram-sage-training is a free, open-source machine learning tool by KingHsp, written mainly in HTML. The 2026 VRAM-Smart Fine-Tuning Suite for SDXL and ANIMA on 12GB GPUs. It has 56 GitHub stars and 0 forks, and was last updated today. GitHub doesn't detect a standard license, so check the repository before using it commercially. According to the project, it needs a GPU with at least 12 GB of memory.
- License
- Not detected
- Commercial use
- No license
- Language
- HTML
- Stars
- 56
- Last update
- today
- Runs on Mac
- Not stated
- GPU
- 12 GB+ (as stated by the project)
- Paid API key
- Not stated
- Self-hostable
- Not stated
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vram-sage-training FAQ
Can I use vram-sage-training commercially?
Unclear. No license was detected, which legally means all rights are reserved. Ask the author before using it commercially. This is a plain-English summary, not legal advice.
Is vram-sage-training free?
Yes. vram-sage-training is open source and free to use. GitHub doesn't detect a standard license, so check the repository before using it commercially.
Does vram-sage-training run on a Mac?
The project doesn't say. Check its installation guide before you start.
Does vram-sage-training need a GPU?
According to the project, vram-sage-training needs a GPU with at least 12 GB of memory.
Is vram-sage-training still maintained?
Yes. It was last updated today and has 0 open issues on GitHub.
What are alternatives to vram-sage-training?
Similar free, open-source tools include LlamaFactory, pytorch-lightning, OneTrainer, lora-scripts.