Top2Vec learns jointly embedded topic, document and word vectors.
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Updated
Nov 14, 2024 - Python
Top2Vec learns jointly embedded topic, document and word vectors.
Efficient few-shot learning with Sentence Transformers
MTEB: Massive Text Embedding Benchmark
A Heterogeneous Benchmark for Information Retrieval. Easy to use, evaluate your models across 15+ diverse IR datasets.
Efficient Retrieval Augmentation and Generation Framework
Running Llama 2 and other Open-Source LLMs on CPU Inference Locally for Document Q&A
unified embedding model
An editing tool that uses AI to transcribe, understand content and search for anything in your footage, integrated with ChatGPT and other AI models
Empower Large Language Models (LLM) using Knowledge Graph based Retrieval-Augmented Generation (KG-RAG) for knowledge intensive tasks
The Fastest State-of-the-Art Static Embeddings in the World
Code for the NAACL 2022 long paper "DiffCSE: Difference-based Contrastive Learning for Sentence Embeddings"
MinT: Minimal Transformer Library and Tutorials
This repository contains an easy and intuitive approach to few-shot classification using sentence-transformers or spaCy models, or zero-shot classification with Huggingface.
sentence-transformers to onnx 让sbert模型推理效率更快
Making BERT stretchy. Semantic Elasticsearch with Sentence Transformers
Simply, faster, sentence-transformers
Open Source Text Embedding Models with OpenAI Compatible API
Rust port of sentence-transformers (https://github.com/UKPLab/sentence-transformers)
A convenient way to link, deduplicate, aggregate and cluster data(frames) in Python using deep learning
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