@0x0SojalSec: Imagine fine-tuning a 31B parameter multimodal model for free,, on Kaggle. Now you can train this massive 31B dense mul…
Summary
Unsloth enables free fine-tuning of a 31B parameter multimodal model on Kaggle using 4-bit quantization, requiring only 22-24GB VRAM for local runs.
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Cached at: 06/20/26, 02:37 PM
Imagine fine-tuning a 31B parameter multimodal model for free,, on Kaggle.
Now you can train this massive 31B dense multimodal powerhouse with efficient 4-bit quantization (text, image, audio) without burning cash on GPUs.
Perfect for custom agents, domain-specific models, or next-level experiments.
You can even run it locally on just 22-24GB VRAM. Custom agents, vision tasks, or your own data all unlocked.
Whether you’re building specialized assistants or pushing open model boundaries
Game changer for researchers Faster training, lower memory, full control.
- http://kaggle.com/code/danielhanchen/gemma4-31b-unsloth…
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