realtonypark

Tony (Seunghyeon) Park 's starred repositories

Perplexica

Perplexica is an AI-powered search engine. It is an Open source alternative to Perplexity AI

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jina

☁️ Build multimodal AI applications with cloud-native stack

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football-ball-possession-project

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CSGHub is an open-source large model platform just like on-premise version of Hugging Face. You can easily manage models and datasets, deploy model applications and setup model finetune or inference jobs with user interface. CSGHub also provides Python SDK with full compatibility of hf sdk. Join us together to build a safer and more open platform⭐️

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llama_index

LlamaIndex is a data framework for your LLM applications

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historical code from reddit.com

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llama3

The official Meta Llama 3 GitHub site

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raft

RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.

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awesome-vector-search

Collections of vector search related libraries, service and research papers

MIT139900

llm.c

LLM training in simple, raw C/CUDA

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recognize-anything

Open-source and strong foundation image recognition models.

Language:Jupyter NotebookApache-2.0280300

towhee

Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.

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Graph-Recommender-FAISS-ECommerce

Graph based recommender system using FAISS for e-commerce depending on purchase and search history.

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faiss

A library for efficient similarity search and clustering of dense vectors.

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trident

A performance library for machine learning applications.

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honeybee

Official implementation of project Honeybee (CVPR 2024)

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milvus

A cloud-native vector database, storage for next generation AI applications

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MovieLens-100K_Recommender-System

Movie recommender system using Surprise library.

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recommend_system_learning

neteasy music recommend system based on Surprise libaray and word2vec model using gensim library

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books2rec

A recommender system built for book lovers.

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RecSys2019_DeepLearning_Evaluation

This is the repository of our article published in RecSys 2019 "Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches" and of several follow-up studies.

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Hybrid-Weighted-Embedding-Recommender

A Hybrid Recommendation system which uses Content embeddings and augments them with collaborative features. Weighted Combination of embeddings enables solving cold start with fast training and serving

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Deep-Learning-Model-for-Hybrid-Recommendation-Engine

A Hybrid recommendation engine built on deep learning architecture, which has the potential to combine content-based and collaborative filtering recommendation mechanisms using a deep learning supervisor

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