[ICLR2025 Spotlight] MagicPIG: LSH Sampling for Efficient LLM Generation
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Updated
Dec 16, 2024 - Python
[ICLR2025 Spotlight] MagicPIG: LSH Sampling for Efficient LLM Generation
Locality Sensitive Hashing, fuzzy-hash, min-hash, simhash, aHash, pHash, dHash。基于 Hash值的图片相似度、文本相似度
一个基于 fasttext + faiss 的商品内容相关推荐实现,nginx+uwsgi+flask / gunicorn+uvicorn+fastapi 提供api查询接口,增加Spark实现 Ansj+Word2vec+LSH+Phoenix
A Query Efficient Natural Language Attack in a Black Box Setting
Search your object with hash
Build content-based image retrieval system using deep learning, applied some large scale similarity search technicals like Kdtree, LSH, Faiss.
Implementation of algorithms for big data using python, numpy, pandas.
This repo aims to implement an modular engine for Locality-Sensitive Hashing (LSH).
A Python project implementing shingling, minwise hashing, and locality-sensitive hashing (LSH) for text similarity detection, along with feature engineering and clustering analysis on real-world datasets. Includes code, visualizations, and key insights for efficient data processing and analysis.
Scalable mining of multidimensional time series motifs.
Simple Projects in Data Mining
a Python program that uses LSH (locality-sensitive hashing) to search and retrieve filenames from a csv file that contains similar words to the user's input.
Assignment-2 for CS F469 Information Retrieval Course
Implementing Locality Sensitive Hashing for DNA Sequences.
Finding similar documents using LSH with MapReduce on multi-node Spark Cluster
The assignment comprises two main tasks: implementing LSH to identify similar businesses based on user ratings and developing various collaborative filtering recommendation systems to predict user ratings for businesses.
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