Lists (12)
Stars
20+ high-performance LLMs with recipes to pretrain, finetune and deploy at scale.
Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)
《李宏毅深度学习教程》（李宏毅老师推荐👍，苹果书🍎），PDF下载地址：https://github.com/datawhalechina/leedl-tutorial/releases
This repo includes ChatGPT prompt curation to use ChatGPT and other LLM tools better.
🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), ga…
中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs)
Implementation of the LLaMA language model based on nanoGPT. Supports flash attention, Int8 and GPTQ 4bit quantization, LoRA and LLaMA-Adapter fine-tuning, pre-training. Apache 2.0-licensed.
Awesome resources for in-context learning and prompt engineering: Mastery of the LLMs such as ChatGPT, GPT-3, and FlanT5, with up-to-date and cutting-edge updates. - Professor Yu Liu
Collection of papers using LLaMA as backbone model
Python - 100天从新手到大师
A comprehensive list of awesome contrastive self-supervised learning papers.
Chang Gung University Computer Science / Artificial Intelligence learning material
Learn how to design, develop, deploy and iterate on production-grade ML applications.
A resource for learning about Machine learning & Deep Learning
A collection of resources and papers on Diffusion Models
《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。
Awesome list for research on CLIP (Contrastive Language-Image Pre-Training).
收集 CVPR 最新的成果，包括论文、代码和demo视频等，欢迎大家推荐！Collect the latest CVPR (Conference on Computer Vision and Pattern Recognition) results, including papers, code, and demo videos, etc., and welcome recommendati…
Natural Language Processing Tutorial for Deep Learning Researchers
A curated list of prompt-based paper in computer vision and vision-language learning.
The offical code of "Parameter-Efficient Learning for Text-to-Speech Accent Adaptation"
NYCU-MLLab / Empathetic-Response-Generation-via-Regularized-Q-Learning
Forked from TTS-Research/Empathetic-Response-Generation-via-Regularized-Q-LearningPyTorch Tutorial for Deep Learning Researchers