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Search results for jupyter notebook questions and answers
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4 search results found
Haystack
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12,474
🔍 LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.
Thoughtsource
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680
A central, open resource for data and tools related to chain-of-thought reasoning in large language models. Developed @ Samwald research group: https://samwald.info/
Tensorflow Nlp Tutorial
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432
tensorflow를 사용하여 텍스트 전처리부터, Topic Models, BERT, GPT와 같은 최신 모델의 다운스트림 태스크들을 정리한 Deep Learning NLP 저장소입니다.
Covid Qa
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312
API & Webapp to answer questions about COVID-19. Using NLP (Question Answering) and trusted data sources.
Question Generation
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305
Generating multiple choice questions from text using Machine Learning.
Pygaggle
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302
a gaggle of deep neural architectures for text ranking and question answering, designed for Pyserini
Compact_bilinear_pooling
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176
MatConvNet and Caffe repo with compact bilinear and bilinear pooling functionality added
Gossiping Chinese Corpus
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136
PTT 八卦版問答中文語料
Toolqa
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130
ToolQA, a new dataset to evaluate the capabilities of LLMs in answering challenging questions with external tools. It offers two levels (easy/hard) across eight real-life scenarios.
Bertqa Attention On Steroids
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105
BertQA - Attention on Steroids
Pytorch Question Answering
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102
Important paper implementations for Question Answering using PyTorch
Persianqa
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84
Persian (Farsi) Question Answering Dataset (+ Models)
Simple Qa Emnlp 2018
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79
Code for my EMNLP 2018 paper "SimpleQuestions Nearly Solved: A New Upperbound and Baseline Approach"
Leaderboard
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71
You can find the most recent KGQA benchmark numbers from publications here.
Wikidata Simplequestions
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63
Mapping of the SimpleQuestions dataset to Wikidata
Automix
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56
Mixing Language Models with Self-Verification and Meta-Verification
Comparemodels_trecqa
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55
Compare six baseline deep learning models on TrecQA
Diffmask
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47
Pytorch implementation of DiffMask
Nlp_notebooks
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46
Tensorflow, Pytorch, Huggingface Transformer, Fastai, etc. tutorial Colab Notebooks.
Turkish Bert Nlp Pipeline
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44
Bert-base NLP pipeline for Turkish, Ner, Sentiment Analysis, Question Answering etc.
Pqg
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39
Code for paper title "Learning Semantic Sentence Embeddings using Pair-wise Discriminator" COLING-2018
Knowledge Enabled Textual Entailment
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34
Natural Language Inference is fundamental to many Natural Language Processing applications such as semantic search and question answering. The task of NLI has gained significant attention in the recent times due to the release of fairly large scale, challenging datasets. Present approaches that address NLI are largely focused on learning based on the given text in order to classify whether the given premise entails, contradicts, or is neutral to the given hypothesis. On the other hand, technique
Drfaq
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28
DrFAQ is a plug-and-play question answering NLP chatbot that can be generally applied to any organisation's text corpora.
Sbu Qa
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26
This repository uses pretrain BERT embeddings for transfer learning in QA domain
Verseagility
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21
Ramp up your custom natural language processing (NLP) task, allowing you to bring your own data, use your preferred frameworks and bring models into production.
Questionanswersystem
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20
基于sentence-transformers实现文本转向量的机器人
Deep Embedded Memory Networks
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20
https://arxiv.org/abs/1707.00836
Covid Qa
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17
A collection of COVID-19 question-answer pairs and transformer baselines for evaluating QA models (Official Repository)
Question Answering
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16
Python-based question answering system that utilizes pretrained BERTbased models from Hugging Face's transformers library.
Biomedical Qa
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16
Neural Biomedical Question Answering
Vqa Mxnet Gluon
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16
Har
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15
Code for WWW2019 paper "A Hierarchical Attention Retrieval Model for Healthcare Question Answering"
Dynamic Coattention Network For Squad
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15
Tensorflow implementation of DCN for question answering on the Stanford Question Answering Dataset (SQuAD)
Quran Qa
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15
Our submission for quran QA shared-task. Fortunately, this work achieved the first place among accepted papers.
Seq2seq Chatbot
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13
Chatbot based Seq2Seq model with bidirectional rnn and attention mechanism with tensorflow, trained on Cornell Movie-Dialogs Corpus and deployed on a Flask Server
Indobert Qa
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12
indoBERT Base-Uncased fine-tuned on Translated Squad v2.0
Who Killed Laura Palmer
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12
Simple Question Answering system, based on data crawled from Twin Peaks Wiki. It is built using 🔍 Haystack, an awesome open-source framework for building search systems that work intelligently over large document collections.
Predicting Subjective Features On Qa Websites
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11
Paper: "Predicting Subjective Features from Questions on QA Websites using BERT"
Lleqa
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10
🤖 Long-Form Legal Question Answering with Retrieval-Augmented LLMs.
Qaprediction
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10
DSSM model for question answering
Squad
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10
Explicit Memory
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10
A machine with human-like memory systems.
Kg Llm Interface
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8
Langchain-powered natural language interface to RDF knowledge-graphs.
Inter Iit 11 Devrev
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7
DevRev’s Expert Answers in a Flash Improving Domain-Specific QA
Document Question Answering
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7
This is a document question answering app made with LangChain and deployed on Streamlit where you can upload a .txt or .docx file, ask questions based on the file and an LLM like Falcon-7B or Dolly-V2-3B answers it. ChromaDB is used as the vector database.
Piaf Ml
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7
PIAF v2.0 repo for ML development. Main purpose of this repo is to automatically find the best configuration for a QA pipeline of a partner organisation.
Nlp_projects
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7
Repository for My HuggingFace Natural Language Processing Projects
Vqa Dataaugmentation
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7
Data Augmentation for Visual Question Answering
Qasystem
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7
COMP90042 Project - Question Answering System
Quran Qa
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6
Quran QA
Mucot
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6
MuCoT: Multilingual Contrastive Training for Question-Answering in Low-resource Languages - Accepted at ACL 2022 Workshop
Thesuperquestiontypetopicclassifier
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6
Using SVM to classify questions based on their type and topic
Chapter9
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6
Chapter 9: Attention and Memory Augmented Networks
Practical Llm And Gpt Applications
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6
The repository is aimed at providing practical examples and resources for developers and researchers interested in applying LM and GPT models to real-world NLP problems.
Qald 10
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6
Dynamic Memory Network Plus
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6
Implementation of Dynamic Memory Network Plus for Question-Answering. Tested on Induction tasks of bAbi 10K dataset.
Dynamic Coattention Network
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5
Implementation of Dynamic Coattention Network for Question Answering
Dsci 550 Assignment 1
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5
📧 Analysis of Cyber Phishing Emails: Fraudulent Emails and Social Engineering.
Tweet Sentiment Extraction
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5
(Silver medal - 60th place - Top 3%) Repository for the "Tweet Sentiment Extraction" Kaggle competition.
Tapas Demo
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5
A small demo to show the power of Google's TAPAS
Question_answering_system
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5
Question answering system developed using seq2seq modeling - The SQuAD dataset.
Table Question Answering Demo
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5
Question Answering on Tabular Data with HuggingFace Transformers Pipeline & TAPAS
Deep Natural Language Processing
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5
Curated implementation notebooks and scripts of deep learning based natural language processing tasks and challenges in TensorFlow.
Qnatables An Intelligent Question Answering System
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5
Question Answering System to answer question over tables in a document
Tableqa Chinese
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5
Unsupervised tableQA and databaseQA on chinese finance question and tabular data
Level2 Mrc Level2 Nlp 09
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5
Open-Domain Question Answering(ODQA)
Question Answering System
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5
It uses extensive NLP and ML techniques at its backend for answering descriptive type queries ( currently, the model has been trained only for Data science and Machine Learning Domain ).
Llm Math Education
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5
Retrieval augmented generation for middle-school math question answering and hint generation
Docvqa Gen
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5
Question Answering dataset generator of Document Visual in English and Chinese
Shortcutlearnability
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5
The official implementation of "Which Shortcut Solution Do Question Answering Models Prefer to Learn?" (AAAI-23)
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