There are 0 repository under peft-fine-tuning-llm topic.
[SIGIR'24] The official implementation code of MOELoRA.
Official code implemtation of paper AntGPT: Can Large Language Models Help Long-term Action Anticipation from Videos?
CRE-LLM: A Domain-Specific Chinese Relation Extraction Framework with Fine-tuned Large Language Model
High Quality Image Generation Model - Comes Under NGC Models @prithivmlmods
Mistral and Mixtral (MoE) from scratch
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.
PEFT is a wonderful tool that enables training a very large model in a low resource environment. Quantization and PEFT will enable widespread adoption of LLM.
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
Fine Tuning pegasus and flan-t5 pre-trained language model on dialogsum datasets for conversation summarization to to optimize context window in RAG-LLMs
Stumble upon a fine tuning that is unfathomable.
This repo contains everything about transformers and NLP.
A QLoRA+ LLM Ensemble with Schema-Linking for Text-to-SQL Generation
LLM projects
This project is an implementation of the paper: Parameter-Efficient Transfer Learning for NLP, Houlsby [Google], ICML 2019.
Fine-tuning Llama3 8b to generate JSON formats for arithmetic questions and process the output to perform calculations.
A fine-tuned LLM great at answering questions about car repairs and maintenance.
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.
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.