simpo-training

Simple Preference Optimization for LLM alignment. Reference-free alternative to DPO with better performance (+6.4 points on AlpacaEval 2.0). No reference model needed, more efficient than DPO. Use for preference alignment when want simpler, faster training than DPO/PPO.

[Post-TrainingSimPOPreferenceOptimization

PoorRican

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fine-tuning-with-trl

TRL: SFT, DPO, PPO, GRPO, reward modeling for LLM RLHF.

[Post-TrainingTRLReinforcementLearning

PoorRican

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huggingface-tokenizers

Fast tokenizers optimized for research and production. Rust-based implementation tokenizes 1GB in <20 seconds. Supports BPE, WordPiece, and Unigram algorithms. Train custom vocabularies, track alignments, handle padding/truncation. Integrates seamlessly with transformers. Use when you need high-performance tokenization or custom tokenizer training.

[TokenizationHuggingFaceBPEWordPiece

PoorRican

0