Search Results for "python text"
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23 projects for "python text" with 2 filters applied:
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Text-to-image Playground
A playground to generate images from any text prompt using SD
dalle-playground is an open-source web application that allows users to generate images from natural language text prompts using modern text-to-image generative models. Originally built around DALL-E Mini, the project later transitioned to using Stable Diffusion, enabling more detailed and higher-quality image synthesis. The system combines a backend machine learning service with a browser-based frontend interface that lets users experiment interactively with prompt engineering and... -
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SimpleHTR
Handwritten Text Recognition (HTR) system implemented with TensorFlow
SimpleHTR is an open-source implementation of a handwriting text recognition system based on deep learning techniques. The project focuses on converting images of handwritten text into machine-readable digital text using neural networks. The system uses a combination of convolutional neural networks and recurrent neural networks to extract visual features and model sequential character patterns in handwriting. It also employs connectionist temporal classification (CTC) to align predicted... -
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The Hundred-Page Machine Learning Book
The Python code to reproduce illustrations from Machine Learning Book
The Hundred-Page Machine Learning Book is the official companion repository for The Hundred-Page Machine Learning Book written by machine learning researcher Andriy Burkov. The repository contains Python code used to generate the figures, visualizations, and illustrative examples presented in the book. Its purpose is to help readers better understand the concepts explained in the text by allowing them to run and experiment with the underlying code themselves. The book itself provides a concise overview of machine learning theory and practice, covering topics such as supervised learning, unsupervised learning, neural networks, and optimization algorithms. ... -
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Natural Language Toolkit
NLTK Source
The Natural Language Toolkit (NLTK) is a widely used open-source Python library designed for working with human language data and building natural language processing (NLP) applications. It provides a comprehensive suite of modules, datasets, and tutorials that support both symbolic and statistical approaches to language processing. The toolkit includes implementations of many foundational NLP algorithms and utilities, enabling developers to perform tasks such as tokenization, stemming,... -
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MEDIUM_NoteBook
Repository containing notebooks of my posts on Medium
...The project is useful for learners who want to explore machine learning concepts interactively using Python and common data science libraries. -
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Machine learning basics
Plain python implementations of basic machine learning algorithms
...The repository includes notebooks that demonstrate classic algorithms such as linear regression, logistic regression, k-nearest neighbors, decision trees, support vector machines, and clustering techniques. Each notebook typically combines explanatory text, Python code, and visualizations to illustrate how the algorithm operates and how it can be applied to datasets. -
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Advanced NLP with spaCy
Advanced NLP with spaCy: A free online course
Advanced NLP with spaCy is an open-source educational repository that provides the materials for an interactive course on advanced natural language processing using the spaCy library. The course is designed to teach developers how to build real-world NLP systems by combining rule-based techniques with machine learning models. The repository includes lessons, exercises, and examples that guide learners through tasks such as tokenization, named entity recognition, text classification, and... -
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Semantra
Multi-tool for semantic search
Semantra is an open-source semantic search tool designed to help users explore large collections of documents by meaning rather than simple keyword matching. The software analyzes text and PDF documents stored locally and creates embeddings that allow queries to retrieve results based on conceptual similarity. It is primarily intended for individuals who need to extract insights from large document collections, including researchers, journalists, students, and historians. The system runs... -
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Google Research: Language
Shared repository for open-sourced projects from the Google AI Lang
Google Research: Language is a shared repository maintained by Google Research that contains open-source projects developed by the Google AI Language team. The repository hosts multiple subprojects related to natural language processing, machine learning, and large-scale language understanding systems. Many of the projects included in the repository correspond to research papers released by Google researchers and provide implementations of new NLP algorithms or experimental frameworks. These... -
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MLX Engine
LM Studio Apple MLX engine
MLX Engine is the Apple MLX-based inference backend used by LM Studio to run large language models efficiently on Apple Silicon hardware. Built on top of the mlx-lm and mlx-vlm ecosystems, the engine provides a unified architecture capable of supporting both text-only and multimodal models. Its design focuses on high-performance on-device inference, leveraging Apple’s MLX stack to accelerate computation on M-series chips. The project introduces modular VisionAddOn components that allow image... -
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OpenMLSys-ZH
Machine Learning Systems: Design and Implementation
This repository is the Chinese translation (or localization) of the OpenMLSys project documentation. Its aim is to make the technical content, tutorials, architecture descriptions, and user guides of the OpenMLSys system more accessible to Chinese-speaking users. The repo mirrors the structure of the original OpenMLSys docs: sections on system design, API references, deployment instructions, module overviews, and example workflows. It helps bridge language barriers in open machine learning... -
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AutoTrain Advanced
Faster and easier training and deployments
AutoTrain Advanced is an open-source machine learning training framework developed by Hugging Face that simplifies the process of training and fine-tuning state-of-the-art AI models. The project provides a no-code and low-code interface that allows users to train models using custom datasets without needing extensive expertise in machine learning engineering. It supports a wide range of tasks including text classification, sequence-to-sequence modeling, token classification, sentence... -
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Jina-Serve
Build multimodal AI applications with cloud-native stack
Jina Serve is an open-source framework designed for building, deploying, and scaling AI services and machine learning pipelines in production environments. The framework allows developers to create microservices that expose machine learning models through APIs that communicate using protocols such as HTTP, gRPC, and WebSockets. It is built with a cloud-native architecture that supports deployment on local machines, containerized environments, or large orchestration platforms such as... -
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seq2seq-couplet
Play couplet with seq2seq model
seq2seq-couplet is a deep learning application that generates Chinese couplet responses using a sequence-to-sequence model built with TensorFlow. Its purpose is not general machine translation, but a specialized text generation task in which the model produces a matching second line for a given first line in the style of traditional couplets. The repository includes the code needed to train the model, configure file paths and hyperparameters, and evaluate progress through loss and BLEU score... -
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FlexLLMGen
Running large language models on a single GPU
FlexLLMGen is an open-source inference engine designed to run large language models efficiently on limited hardware resources such as a single GPU. The system focuses on high-throughput generation workloads where large batches of text must be processed quickly, such as large-scale data extraction or document analysis tasks. Instead of requiring expensive multi-GPU systems, the framework uses techniques such as memory offloading, compression, and optimized batching to run large models on... -
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TensorFlow Hub
A library for transfer learning by reusing parts of TensorFlow models
TensorFlow Hub is a repository that provides a library and platform for publishing, discovering, and reusing pre-trained machine learning models built with TensorFlow. The project enables developers to integrate high-quality models into their applications without needing to train them from scratch. Through TensorFlow Hub, researchers and practitioners can share reusable model components such as image classifiers, text embedding models, and object detection networks. These models can be... -
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Promptify
se GPT or other prompt based models to get structured output
...This approach allows developers to perform tasks such as text classification, named entity recognition, question answering, and information extraction using consistent prompt templates. The library supports integration with multiple large language model providers, enabling users to experiment with various models without changing their overall workflow. -
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picoGPT
An unnecessarily tiny implementation of GPT-2 in NumPy
picoGPT is a minimal implementation of the GPT-2 language model designed to demonstrate how transformer-based language models work at a conceptual level. The repository focuses on educational clarity rather than production performance, implementing the core components of the GPT architecture in a concise and readable way. It allows users to understand how tokenization, transformer layers, attention mechanisms, and autoregressive text generation operate in modern large language models. The... -
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d2l-zh
Chinese-language edition of Dive into Deep Learning
d2l‑zh is the Chinese-language edition of Dive into Deep Learning, an interactive, open‑source deep learning textbook that combines code, math, and explanatory text. It features runnable Jupyter notebooks compatible with multiple frameworks (e.g., PyTorch, MXNet, TensorFlow), comprehensive theoretical analysis, and exercises. Widely adopted in over 70 countries and used by more than 500 universities for teaching deep learning. -
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Pattern Recognition and Machine Learning
Repository of notes, code and notebooks in Python
Pattern Recognition and Machine Learning is an open-source repository that provides Python implementations and interactive notebooks for algorithms presented in the book Pattern Recognition and Machine Learning by Christopher Bishop. The project recreates many of the mathematical concepts and diagrams from the book using executable Jupyter notebooks, allowing readers to experiment directly with the algorithms described in the text. -
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NLP-Models-Tensorflow
Gathers machine learning and Tensorflow deep learning models for NLP
NLP-Models-Tensorflow is a collection of natural language processing model implementations built using the TensorFlow deep learning framework. The repository provides numerous examples of neural network architectures used in modern NLP research and applications, including text classification, language modeling, machine translation, and sentiment analysis. Each model implementation is designed to illustrate how common NLP architectures operate, such as recurrent neural networks, convolutional... -
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ELI5
A library for debugging/inspecting machine learning classifiers
ELI5 is a Python library designed to help developers interpret, debug, and explain the predictions of machine learning models. The project focuses on improving model transparency by providing tools that visualize feature importance and prediction reasoning. It supports several popular machine learning frameworks including scikit-learn, XGBoost, LightGBM, CatBoost, and Keras. -
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Generative Models
Collection of generative models, e.g. GAN, VAE in Pytorch
This project is a comprehensive open-source collection of implementations of various generative machine learning models designed to help researchers and developers experiment with deep generative techniques. The repository contains practical implementations of well-known architectures such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), Restricted Boltzmann Machines, and Helmholtz Machines, implemented primarily using modern deep learning frameworks like PyTorch...
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