Monolingual or Multilingual Instruction Tuning: Which Makes a Better Alpaca
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Updated
Mar 6, 2024 - Python
Monolingual or Multilingual Instruction Tuning: Which Makes a Better Alpaca
EasyRLHF aims to provide an easy and minimal interface to train aligned language models, using off-the-shelf solutions and datasets
Evaluating Large Language Models with Instructions and Prompts
an instruction-tuning dataset generation script
Random Noisy Embeddings with fine-tuning 방법론을 한국어 LLM에 간단히 적용할 수 있는 Kosy🍵llama
Instruction and training dataset generation using Mistral 7B with context from document chunks
Vision Large Language Models trained on M3IT instruction tuning dataset
The official implementation of paper "Demystifying Instruction Mixing for Fine-tuning Large Language Models"
This repo is the official implementation for Incubating Text Classifiers Following User Instruction with Nothing but LLM. We allow users to get a personalized classifier with only the instruction as input. The incubation is based on a llama-2-7b fine-tuned on Huggingface Meta Data and Self-Diversification.
"RecRanker: Instruction Tuning Large Language Model as Ranker for Top-k Recommendation"
This repository has a lot of LLM projects done. It is the best place to start learning LLM.
Code base for the paper "Instruction Tuned Models are Quick Learners".
[arXiv preprint 2024] Official code release accompanying the paper "diff History for Neural Language Agents" (Piterbarg, Pinto, Fergus)
MUFFIN: Curating Multi-Faceted Instructions for Improving Instruction-Following
Source code of paper 'Aligning Instruction Tasks Unlocks Large Language Models as Zero-Shot Relation Extractors' (ACL 2023 Findings)
Okapi: Instruction-tuned Large Language Models in Multiple Languages with Reinforcement Learning from Human Feedback
🌱 梦想家(DreamerGPT):中文大语言模型指令精调
An open-source conversational language model developed by the Knowledge Works Research Laboratory at Fudan University.
Multimodal Instruction Tuning for Llama 3
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