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Research#llm📝 BlogAnalyzed: Dec 28, 2025 12:13

Troubleshooting LoRA Training on Stable Diffusion with CUDA Errors

Published:Dec 28, 2025 12:08
1 min read
r/StableDiffusion

Analysis

This Reddit post describes a user's experience troubleshooting LoRA training for Stable Diffusion. The user is encountering CUDA errors while training a LoRA model using Kohya_ss with a Juggernaut XL v9 model and a 5060 Ti GPU. They have tried various overclocking and power limiting configurations to address the errors, but the training process continues to fail, particularly during safetensor file generation. The post highlights the challenges of optimizing GPU settings for stable LoRA training and seeks advice from the Stable Diffusion community on resolving the CUDA-related issues and completing the training process successfully. The user provides detailed information about their hardware, software, and training parameters, making it easier for others to offer targeted suggestions.
Reference

It was on the last step of the first epoch, generating the safetensor file, when the workout ended due to a CUDA failure.

Research#llm👥 CommunityAnalyzed: Jan 4, 2026 08:14

Overclocking LLM Reasoning: Monitoring and Controlling LLM Thinking Path Lengths

Published:Jul 6, 2025 12:53
1 min read
Hacker News

Analysis

This article likely discusses techniques to optimize the reasoning process of Large Language Models (LLMs). The term "overclocking" suggests efforts to improve performance, while "monitoring and controlling thinking path lengths" indicates a focus on managing the complexity and efficiency of the LLM's reasoning steps. The source, Hacker News, suggests a technical audience interested in advancements in AI.

Key Takeaways

    Reference