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Full finetuning of large language models without large memory requirements

Unlock the potential of finetuning Large Language Models (LLMs). Learn from industry expert, and discover when to apply finetuning, data preparation techniques, and how to effectively train and evaluate LLMs.

Finetuning large language models (LLMs) for vulnerability detection

Mispronunciation Detection using a pretrained and finetuned wav2vec2 model for phoneme recognition and diagnosis and feedback using large language model

Supplementary material for "Understanding Parameter-Efficient Finetuning of Large Language Models: From Prefix Tuning to Adapters"

A Gradio web UI for Large Language Models. Supports LoRA/QLoRA finetuning,RAG(Retrieval-augmented generation) and Chat

This repository benchmark Ntropy API against different Large Language Models (OpenAI ChatGPT and LLAMA finetuned models). It also contains an easy to use wrapper to enable using the LLMs to perform transaction enrichment. Llama adapters were open sourced and are available on huggingface hub.

This repository contains the implementation for our EMNLP 2023 paper: HoneyBee: Progressive Instruction Finetuning of Large Language Models for Materials Science

Finetuning Generative Large Language Models with Discrimination Instructions for Knowledge Graph Completion, ISWC 2024

QAmeleon introduces synthetic multilingual QA data using PaLM, a 540B large language model. This dataset was generated by prompt tuning PaLM with only five examples per language. We use the synthetic data to finetune downstream QA models leading to improved accuracy in comparison to English-only ... Read more