repoGitHubTrust 82 · PrimaryPublished 1mo agoLive · 1mo ago
Yog-Sotho/LLM-fine-tuner
Powerful no-code LLM fine-tuner: upload data → train → deploy in minutes. Unsloth 2-5× acceleration · QLoRA/DPO/RLHF/PPO/ORPO · Reward Model training · GGUF export · vLLM inference · BLEU/ROUGE/BERTScore · full CLI · Heretic Mode to unlock full model potential
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Paper → model → repo connections mined from source citations (Tier-1 exact match).
Why these links exist
Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.
- PossiblePossibly related (embedding) · 54%Fine-tuning →
- PossiblePossibly related (embedding) · 50%DynaMiCS: Fine-Tuning LLMs with Performance Constraints Using Dynamic Mixtures - Apple Machine Learning Research →
- PossiblePossibly related (embedding) · 50%IEEE Rolls Out Large Language Models Virtual Training Course →
- PossiblePossibly related (embedding) · 49%Fine-tune a small model on your own data →
- PossiblePossibly related (embedding) · 49%OpenAI and Broadcom unveil LLM-optimized inference chip →
- PossiblePossibly related (embedding) · 50%Verifiers v1 Lets Agentic RL Training Exceed Model Context Windows via DAG Branching - Tech Times →
- PossiblePossibly related (embedding) · 50%High-Efficiency LLM Models - Trend Hunter →
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tutorialFine-tune a small model on your own dataglossary_termFine-tuningnewsOpenAI and Broadcom unveil LLM-optimized inference chipnewsDynaMiCS: Fine-Tuning LLMs with Performance Constraints Using Dynamic Mixtures - Apple Machine Learning ResearchnewsVerifiers v1 Lets Agentic RL Training Exceed Model Context Windows via DAG Branching - Tech TimesnewsHigh-Efficiency LLM Models - Trend HunternewsIEEE Rolls Out Large Language Models Virtual Training Course