Infinity is a high-throughput, low-latency serving engine for text-embeddings, reranking models, clip, clap and colpali
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Updated
Jun 6, 2025 - Python
Infinity is a high-throughput, low-latency serving engine for text-embeddings, reranking models, clip, clap and colpali
💭 Aspect-Based-Sentiment-Analysis: Transformer & Explainable ML (TensorFlow)
NLP for human. A fast and easy-to-use natural language processing (NLP) toolkit, satisfying your imagination about NLP.
Simple State-of-the-Art BERT-Based Sentence Classification with Keras / TensorFlow 2. Built with HuggingFace's Transformers.
pretrained BERT model for cyber security text, learned CyberSecurity Knowledge
This repository contains PyTorch implementation for the baseline models from the paper Utterance-level Dialogue Understanding: An Empirical Study
文本相似度,语义向量,文本向量,text-similarity,similarity, sentence-similarity,BERT,SimCSE,BERT-Whitening,Sentence-BERT, PromCSE, SBERT
Bilingual term extractor
Hierarchical-Attention-Network
This is the code for loading the SenseBERT model, described in our paper from ACL 2020.
Topic clustering library built on Transformer embeddings and cosine similarity metrics.Compatible with all BERT base transformers from huggingface.
An easy-to-use Python module that helps you to extract the BERT embeddings for a large text dataset (Bengali/English) efficiently.
A Robustly Optimized BERT Pretraining Approach for Vietnamese
Code and CoarseWSD-20 datasets for "Language Models and Word Sense Disambiguation: An Overview and Analysis"
Contextual knowledge bases
COVID-19 Question Dataset from the paper "What Are People Asking About COVID-19? A Question Classification Dataset"
Problem Statement: Given the tweets from customers about various tech firms who manufacture and sell mobiles, computers, laptops, etc, the task is to identify if the tweets have a negative sentiment towards such companies or products.
Recommendation engine framework based on Wikipedia data
A showcase of combining Elasticsearch with BERT on the HackerNews public data
[COLING 2020] BERT-based Models for Chengyu
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