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HLLM: Enhancing Sequential Recommendations via Hierarchical Large Language Models for Item and User Modeling
Qwen2.5 is the large language model series developed by Qwen team, Alibaba Cloud.
Repository hosting code for "Actions Speak Louder than Words: Trillion-Parameter Sequential Transducers for Generative Recommendations" (https://arxiv.org/abs/2402.17152).
The simplest, fastest repository for training/finetuning medium-sized GPTs.
Minimal, clean code for the Byte Pair Encoding (BPE) algorithm commonly used in LLM tokenization.
Official PyTorch Implementation of "Scalable Diffusion Models with Transformers"
推荐/广告/搜索领域工业界经典以及最前沿论文集合。A collection of industry classics and cutting-edge papers in the field of recommendation/advertising/search.
Processing and analysis of patch clamp electrophysiology data
This repository collects debiasing methods for recommendation
Source code for Twitter's Recommendation Algorithm
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.
GPT4All: Run Local LLMs on Any Device. Open-source and available for commercial use.
Making large AI models cheaper, faster and more accessible
A personal knowledge management and sharing system for VSCode
High-Resolution Image Synthesis with Latent Diffusion Models
Implementation of RLHF (Reinforcement Learning with Human Feedback) on top of the PaLM architecture. Basically ChatGPT but with PaLM
A curated collection of resources and research related to the geometry of representations in the brain, deep networks, and beyond
Open Bandit Pipeline: a python library for bandit algorithms and off-policy evaluation
Code behind the work "Single Cortical Neurons as Deep Artificial Neural Networks", published in Neuron 2021
☁️ Build multimodal AI applications with cloud-native stack
🚀 A simple way to launch, train, and use PyTorch models on almost any device and distributed configuration, automatic mixed precision (including fp8), and easy-to-configure FSDP and DeepSpeed support
SpikingJelly is an open-source deep learning framework for Spiking Neural Network (SNN) based on PyTorch.
An elegant PyTorch deep reinforcement learning library.
This package contains deep learning models and related scripts for RoseTTAFold
Reinforced Recommendation toolkit built around pytorch 1.7
A cheatsheet of modern C++ language and library features.
Learn how to design, develop, deploy and iterate on production-grade ML applications.