Search Results for "python language" - Page 41
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Showing 1084 open source projects for "python language"
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Dragonfire
The open-source virtual assistant for Ubuntu based Linux distributions
Dragonfire is the open-source virtual assistant project for Ubuntu-based Linux distributions. Her main objective is to serve as a command and control interface to the helmet user. So that you will be able to give orders just by using your voice commands and your eye movements. That makes the helmet handsfree. We are planning to ship Dragonfire as a preinstalled software package on DragonOS Linux Distribution. DragonOS will be a Linux distribution specially designed for the helmet. It will... -
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Texar
Toolkit for Machine Learning, Natural Language Processing
Texar is a toolkit aiming to support a broad set of machine learning, especially natural language processing and text generation tasks. Texar provides a library of easy-to-use ML modules and functionalities for composing whatever models and algorithms. The tool is designed for both researchers and practitioners for fast prototyping and experimentation. Texar was originally developed and is actively contributed by Petuum and CMU in collaboration with other institutes. A mirror of this... -
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Deep Learning Drizzle
Drench yourself in Deep Learning, Reinforcement Learning
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures! Optimization courses which form the foundation for ML, DL, RL. Computer Vision courses which are DL & ML heavy. Speech recognition courses which are DL heavy. Structured Courses on Geometric, Graph Neural Networks. Section on Autonomous Vehicles. Section on Computer Graphics with ML/DL focus. -
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gpt2-client
Easy-to-use TensorFlow Wrapper for GPT-2 117M, 345M, 774M, etc.
GPT-2 is a Natural Language Processing model developed by OpenAI for text generation. It is the successor to the GPT (Generative Pre-trained Transformer) model trained on 40GB of text from the internet. It features a Transformer model that was brought to light by the Attention Is All You Need paper in 2017. The model has 4 versions - 124M, 345M, 774M, and 1558M - that differ in terms of the amount of training data fed to it and the number of parameters they contain. Finally, gpt2-client is a... -
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InferSent
InferSent sentence embeddings
InferSent is a supervised sentence embedding method that learns universal representations from Natural Language Inference data and transfers well to many downstream tasks. It uses a BiLSTM encoder with max-pooling to produce fixed-length sentence vectors that capture semantics beyond bag-of-words statistics. Trained on large NLI datasets, the embeddings generalize across tasks like sentiment analysis, entailment, paraphrase detection, and semantic similarity with simple linear classifiers.... -
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MMF
A modular framework for vision & language multimodal research
MMF is a modular framework for vision and language multimodal research from Facebook AI Research. MMF contains reference implementations of state-of-the-art vision and language models and has powered multiple research projects at Facebook AI Research. MMF is designed from ground up to let you focus on what matters, your model, by providing boilerplate code for distributed training, common datasets and state-of-the-art pre-trained baselines out-of-the-box. MMF is built on top of PyTorch that... -
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Project Malmo
A platform for Artificial Intelligence experimentation on Minecraft
How can we develop artificial intelligence that learns to make sense of complex environments? That learns from others, including humans, how to interact with the world? That learns transferable skills throughout its existence, and applies them to solve new, challenging problems? Project Malmo sets out to address these core research challenges, addressing them by integrating (deep) reinforcement learning, cognitive science, and many ideas from artificial intelligence. The Malmo platform... -
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Defox text to speech and downloader
Written or imported text offline read or online download.
...Therefore maybe I haven't software making skills. I'm worried about that. ! Note 2 : When you double click on the software maybe it will get some seconds to open. That's not my fault. I used Python language to make this software and Python was not supported speedy to modern computers. -
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Safe Harbor Deidentification
Safe Harbor Deidentification for medical documents
Phalanx - Deidentify Safe Harbor Deidentification Mode of Phalanx is an abridged pipeline of NLP annotators culminating in NER annotators which write output of text offsets. It uses the Safe Harbor deidentification method. -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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GPT2-Pytorch with Text-Generator
Simple Text-Generator with OpenAI gpt-2 Pytorch Implementation
GPT-2 PyTorch is a compact educational implementation of OpenAI’s GPT-2 text generator in PyTorch. It uses pretrained weights converted for PyTorch rather than training the language model from scratch. Users can begin generation from a supplied prompt or request unconditional samples. Command-line options control sample count, batch size, output length, temperature, and top-k filtering. The repository includes a runnable Python script, dependency file, and Google Colab notebook for faster experimentation. It is best suited to studying an early Transformer language model and its sampling process rather than building a modern production system. -
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NeuroNER
Named-entity recognition using neural networks
Named-entity recognition (NER) aims at identifying entities of interest in the text, such as location, organization and temporal expression. Identified entities can be used in various downstream applications such as patient note de-identification and information extraction systems. They can also be used as features for machine learning systems for other natural language processing tasks. Leverages the state-of-the-art prediction capabilities of neural networks (a.k.a. "deep learning") Is... -
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lazynlp
Library to scrape and clean web pages to create massive datasets
LazyNLP is a lightweight tool for collecting and curating large-scale text datasets for machine learning and NLP applications with minimal manual effort. -
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Python Data Science Tutorials
Common data analysis and machine learning tasks using python
Python Data Science Tutorials is a curated learning repository for common data analysis, machine learning, and natural language processing tasks in Python. It combines external tutorials, courses, reference guides, notebooks, articles, and selected code examples. The collection begins with Python fundamentals and then moves into scientific computing, statistics, NumPy, pandas, data exploration, and visualization. -
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TextRank
TextRank implementation for Python 3
TextRank is an implementation of the TextRank algorithm for extractive text summarization and keyword extraction, inspired by Google’s PageRank. -
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Arabic Corpus
Text categorization, arabic language processing, language modeling
The Arabic Corpus {compiled by Dr. Mourad Abbas ( http://sites.google.com/site/mouradabbas9/corpora ) The corpus Khaleej-2004 contains 5690 documents. It is divided to 4 topics (categories). The corpus Watan-2004 contains 20291 documents organized in 6 topics (categories). Researchers who use these two corpora would mention the two main references: (1) For Watan-2004 corpus ---------------------- M. Abbas, K. Smaili, D. Berkani, (2011) Evaluation of Topic Identification Methods on... -
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Finetune Transformer LM
Code for "Improving Language Understanding by Generative Pre-Training"
finetune-transformer-lm is a research codebase that accompanies the paper “Improving Language Understanding by Generative Pre-Training,” providing a minimal implementation focused on fine-tuning a transformer language model for evaluation tasks. The repository centers on reproducing the ROCStories Cloze Test result and includes a single-command training workflow to run the experiment end to end. It documents that runs are non-deterministic due to certain GPU operations and reports a median... -
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Deepvoice3_pytorch
PyTorch implementation of convolutional neural networks
An open source implementation of Deep Voice 3: Scaling Text-to-Speech with Convolutional Sequence Learning. -
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OpenSeq2Seq
Toolkit for efficient experimentation with Speech Recognition
OpenSeq2Seq is a TensorFlow-based toolkit for efficient experimentation with sequence-to-sequence models across speech and NLP tasks. Its core goal is to give researchers a flexible, modular framework for building and training encoder–decoder architectures while fully leveraging distributed and mixed-precision training. The toolkit includes ready-made models for neural machine translation, automatic speech recognition, speech synthesis, language modeling, and additional NLP tasks such as... -
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CRP - Chemical Reaction Prediction
Predicting Organic Reactions using Neural Networks.
The intend is to solve the forward-reaction prediction problem, where the reactants are known and the interest is in generating the reaction products using Deep learning. This Graphical User Interface takes simplified molecular-input line-entry system (SMILES) as an input and generates the product SMILE & molecule. Beam search is used in Version 2, to generate top 5 predictions. Maximum input length for the model is 15 (excluding spaces). -
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Presage
the intelligent predictive text entry platform
Presage (formerly Soothsayer) is an intelligent predictive text entry system. Presage generates predictions by modelling natural language as a combination of redundant information sources. Presage computes probabilities for words which are most likely to be entered next by merging predictions generated by the different predictive algorithms. Presage's modular and extensible architecture allows its language model to be extended and customized to utilize statistical, syntactic, and semantic... -
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anaGo
Bidirectional LSTM-CRF and ELMo for Named-Entity Recognition
anaGo is a Python library for sequence labeling(NER, PoS Tagging,...), implemented in Keras. anaGo can solve sequence labeling tasks such as named entity recognition (NER), part-of-speech tagging (POS tagging), semantic role labeling (SRL) and so on. Unlike traditional sequence labeling solver, anaGo doesn't need to define any language-dependent features. -
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DeepLearn
Implementation of research papers on Deep Learning+ NLP+ CV in Python
Welcome to DeepLearn. This repository contains an implementation of the following research papers on NLP, CV, ML, and deep learning. The required dependencies are mentioned in requirement.txt. I will also use dl-text modules for preparing the datasets. If you haven't use it, please do have a quick look at it. CV, transfer learning, representation learning. -
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EvalAI
Evaluating state of the art in AI
EvalAI is an open-source platform for evaluating and comparing machine learning (ML) and artificial intelligence (AI) algorithms at scale. We allow the creation of an arbitrary number of evaluation phases and dataset splits, compatibility using any programming language, and organizing results in both public and private leaderboards. Certain large-scale challenges need special computing capabilities for evaluation. If the challenge needs extra computational power, challenge organizers can... -
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PyAIMLng
The Next Generation of Python AIML Interpreter
A Python AIML interpreter with non-compliant extensions. PyAIMLng is an interpreter for AIML (the Artificial Intelligence Markup Language), forked from Cort Stratton's PyAIML. PyAIMLng adds additional features which are not part of the AIML 1.0.1 specification in order to provide the bot master with a rich set of tools from which to build a more believable AIML bot. -
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House3D
A Realistic and Rich 3D Environment
House3D is a large-scale virtual 3D simulation environment designed to support research in embodied AI, reinforcement learning, and vision-language navigation. It provides more than 45,000 richly annotated indoor scenes sourced from the SUNCG dataset, covering diverse architectural layouts such as studios, multi-floor homes, and spaces with detailed furnishings and room types. Each environment includes fully labeled 3D objects, allowing agents to perceive and interact with their surroundings...