LLaMA-TRL: Fine-tuning LLaMA with PPO and LoRA

Notus is a collection of fine-tuned LLMs using SFT, DPO, SFT+DPO, and/or any other RLHF techniques, while always keeping a data-first approach

基于DPO算法微调语言大模型，简单好上手。

Various training, inference and validation code and results related to Open LLM's that were pretrained (full or partially) on the Dutch language.

realize the reinforcement learning training for gpt2 llama bloom and so on llm model

Notebooks to create an instruction following version of Microsoft's Phi 2 LLM with Supervised Fine Tuning and Direct Preference Optimization (DPO)

Supervised Fine tuning using TRL library

Direct Preference Optimization of ChatGPT2 using TRL Library

ODM: TRL to BAL rules automated translation

The overall aim of this project is to create a term rewriting system that could be useful in everyday programming, and to represent data in a way that roughly correspond to the definition of a term in formal logic. Terms should be familiar to any programmer because they are basically constants, variables, and function symbols.

Notebooks to create an instruction following version of Microsoft's Phi 1.5 LLM with Supervised Fine Tuning and Direct Preference Optimization (DPO)

Эксперименты с LLM (инференс, rag, дообучение)