Official implementation of "DoRA: Weight-Decomposed Low-Rank Adaptation"
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Updated
Apr 28, 2024
Official implementation of "DoRA: Weight-Decomposed Low-Rank Adaptation"
[SIGIR'24] The official implementation code of MOELoRA.
Code for NOLA, an implementation of "nola: Compressing LoRA using Linear Combination of Random Basis"
Official code implemtation of paper AntGPT: Can Large Language Models Help Long-term Action Anticipation from Videos?
memory-efficient fine-tuning; support 24G GPU memory fine-tuning 7B
Fine-tune StarCoder2-3b for SQL tasks on limited resources with LORA. LORA reduces model size for faster training on smaller datasets. StarCoder2 is a family of code generation models (3B, 7B, and 15B), trained on 600+ programming languages from The Stack v2 and some natural language text such as Wikipedia, Arxiv, and GitHub issues.
This repository was commited under the action of executing important tasks on which modern Generative AI concepts are laid on. In particular, we focussed on three coding actions of Large Language Models. Extra and necessary details are given in the README.md file.
Using Open-Source LLMs like FLAN-T5, built a Dialog Summarization model and did fine-tuning with DialogSum HF Dataset
Stumble upon a fine tuning that is unfathomable.
Dialogue Summary LLM - FLAN - T5: An implementation of the Flan-t5 LLM to summarize dialogues. Prompt Engineering , Fine tuning with PEFT and fine tuning with RL (PPO) is explored within this project.
This repo contains implementations of fine-tuning LLaMA LLM model using LoRA weights (PEFT) as well as focuses on the Retrieval Augmented Generation (RAG) framework.
A QLoRA+ LLM Ensemble with Schema-Linking for Text-to-SQL Generation
This project is an implementation of the paper: Parameter-Efficient Transfer Learning for NLP, Houlsby [Google], ICML 2019.
This repo contains everything about transformers and NLP.
CRE-LLM: A Domain-Specific Chinese Relation Extraction Framework with Fine-tuned Large Language Model
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