Top2Vec learns jointly embedded topic, document and word vectors.
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Updated
May 12, 2024 - Python
Top2Vec learns jointly embedded topic, document and word vectors.
Running Llama 2 and other Open-Source LLMs on CPU Inference Locally for Document Q&A
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
unified embedding model
Empower Large Language Models (LLM) using Knowledge Graph based Retrieval-Augmented Generation (KG-RAG) for knowledge intensive tasks
An editing tool that uses AI to transcribe, understand content and search for anything in your footage, integrated with ChatGPT and other AI models
FAQ-based Question Answering System using BERT
sentence-transformers to onnx 让sbert模型推理效率更快
Code for the NAACL 2022 long paper "DiffCSE: Difference-based Contrastive Learning for Sentence Embeddings"
Making BERT stretchy. Semantic Elasticsearch with Sentence Transformers
Build Semantic Search with S-BERT and Fine-tune your model in unsupervised way
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.
Open Source Text Embedding Models with OpenAI Compatible API
Rust port of sentence-transformers (https://github.com/UKPLab/sentence-transformers)
Building a model to recognize incentives for landscape restoration in environmental policies from Latin America, the US and India. Bringing NLP to the world of policy analysis through an extensible framework that includes scraping, preprocessing, active learning and text analysis pipelines.
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