Search Results for "text-speaker" - Page 23
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Showing 1790 open source projects for "text-speaker"
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ticket
Fast, powerful, git-native ticket tracking in a single bash script
ticket is a lightweight, git-native ticket management tool implemented as a single Bash script that brings powerful issue tracking directly into your Git workflows without requiring a database or complex setup. It stores each ticket as a Markdown file with YAML frontmatter, making them human-readable and easy to version control alongside your code, while also allowing IDEs to jump straight to ticket definitions. The CLI provides common subcommands to create, list, edit, close, and manage... -
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Open Model Zoo
Pre-trained Deep Learning models and demos
Open Model Zoo is a large repository of high-quality pre-trained deep learning models and demonstration applications designed to work with the OpenVINO™ toolkit, offering a comprehensive starting point for a wide range of AI and computer vision workloads. It includes hundreds of models covering object detection, classification, segmentation, pose estimation, speech recognition, text-to-speech, and more, many of which are already converted into formats optimized for inference on CPUs, GPUs, VPUs, and other accelerators supported by OpenVINO. In addition to model files, Open Model Zoo provides demo applications that show realistic usage patterns and help developers quickly prototype and understand inference pipelines in C++, Python, or via the OpenCV Graph API. ... -
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nanochat
The best ChatGPT that $100 can buy
nanochat is a from-scratch, end-to-end “mini ChatGPT” that shows the entire path from raw text to a chatty web app in one small, dependency-lean codebase. The repository stitches together every stage of the lifecycle: tokenizer training, pretraining a Transformer on a large web corpus, mid-training on dialogue and multiple-choice tasks, supervised fine-tuning, optional reinforcement learning for alignment, and finally efficient inference with caching. -
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Atheris
A Coverage-Guided, Native Python Fuzzer
...The tool integrates smoothly with Python’s packaging and unit-test ecosystems, so you can wrap existing tests as fuzz targets and keep results understandable. It supports structured input strategies and custom mutators, which is especially helpful for text and data formats common in Python workloads. In practice, Atheris compresses weeks of edge-case brainstorming into hours of automated exploration with actionable, minimized reproductions. -
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Mozc Devices
Circuit diagrams and firmware source code for Gboard DIY keyboards
...Each subproject in the repository corresponds to a unique input device prototype, including versions such as the Drum Set, Morse Code, Patapata, Magic Hand, Piropiro, Physical Flick, Puchi Puchi, Nazoru, Mageru, Yunomi, Bar, Caps, Double Sided, and Dial editions. These devices creatively reinterpret how users can interact with Japanese text input, blending humor, engineering, and physical computing. The repository serves as an archive of the schematics, firmware, and PCB designs for these inventive input mechanisms, with many projects including promotional videos and technical references. -
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ML Ferret
Refer and Ground Anything Anywhere at Any Granularity
...The repo presents the vision-language pipeline, model assets, and paper resources that show how Ferret answers questions, follows instructions, and returns grounded outputs rather than just text. In practice, this enables tasks like “find that small red icon next to the chart and describe it” where both the linguistic reference and the visual region are ambiguous without fine spatial reasoning. -
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Multimodal
TorchMultimodal is a PyTorch library
This project, also known as TorchMultimodal, is a PyTorch library for building, training, and experimenting with multimodal, multi-task models at scale. The library provides modular building blocks such as encoders, fusion modules, loss functions, and transformations that support combining modalities (vision, text, audio, etc.) in unified architectures. It includes a collection of ready model classes—like ALBEF, CLIP, BLIP-2, COCA, FLAVA, MDETR, and Omnivore—that serve as reference implementations you can adopt or adapt. The design emphasizes composability: you can mix and match encoder, fusion, and decoder components rather than starting from monolithic models. ... -
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MetaCLIP
ICLR2024 Spotlight: curation/training code, metadata, distribution
MetaCLIP is a research codebase that extends the CLIP framework into a meta-learning / continual learning regime, aiming to adapt CLIP-style models to new tasks or domains efficiently. The goal is to preserve CLIP’s strong zero-shot transfer capability while enabling fast adaptation to domain shifts or novel class sets with minimal data and without catastrophic forgetting. The repository provides training logic, adaptation strategies (e.g. prompt tuning, adapter modules), and evaluation... -
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DreamCraft3D
Official implementation of DreamCraft3D
DreamCraft3D is DeepSeek’s generative 3D modeling framework / model family that likely extends their earlier 3D efforts (e.g. Shap-E or Point-E style models) with more capability, control, or expression. The name suggests a “dream crafting” metaphor—users probably supply textual or image prompts and generate 3D assets (point clouds, meshes, scenes). The repository includes model code, inference scripts, sample prompts, and possibly dataset preparation pipelines. It may integrate rendering or... -
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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Gretel Synthetics
Synthetic data generators for structured and unstructured text
Unlock unlimited possibilities with synthetic data. Share, create, and augment data with cutting-edge generative AI. Generate unlimited data in minutes with synthetic data delivered as-a-service. Synthesize data that are as good or better than your original dataset, and maintain relationships and statistical insights. Customize privacy settings so that data is always safe while remaining useful for downstream workflows. Ensure data accuracy and privacy confidently with expert-grade reports.... -
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Textual
Textual is a TUI (Text User Interface) framework for Python
Textual is a Python framework for creating interactive applications that run in your terminal. Textual adds interactivity to Rich with a Python API inspired by modern web development. On modern terminal software (installed by default on most systems), Textual apps can use 16.7 million colors with mouse support and smooth flicker-free animation. A powerful layout engine and re-usable components makes it possible to build apps that rival the desktop and web experience. Textual runs on Linux,... -
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MCP UI
SDK for building interactive UI components over MCP for AI tools
...It enables developers to create rich, dynamic UI components that can be delivered from an MCP server and rendered seamlessly by a compatible client. Instead of returning only text responses, tools can provide structured UI resources such as HTML or remote-rendered components, allowing more engaging and functional interactions. mcp-ui introduces a standardized approach where tools and their associated interfaces are linked through metadata, enabling clients to automatically discover and display the correct UI. ... -
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news-please
Python tool for crawling and extracting structured data from news site
...It provides an integrated pipeline that crawls news sites, retrieves article pages, and extracts structured information such as headlines, authors, publication dates, and article text. news-please can recursively follow internal links and read RSS feeds to gather both recent and archived articles from a news outlet when given only the root URL of a site. It combines several established technologies and libraries to perform web crawling and content extraction, enabling reliable processing across a wide range of news sources. ... -
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Claude Code Tools
Practical productivity tools for Claude Code, Codex-CLI
Claude Code Tools is an open-source collection of command-line utilities and productivity plugins designed to enhance developer workflows when using AI coding agents such as Claude Code and Codex-CLI. The project focuses on solving common problems encountered in AI-assisted development environments, including managing session history, automating terminal interactions, and maintaining context across multiple coding sessions. It includes tools that allow developers to search conversation logs... -
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Acontext
Context data platform for building observable, self-learning AI agents
Acontext is a cloud-native context data platform designed to support the development and operation of advanced AI agents. It provides a unified system to store and manage contexts, multimodal messages, artifacts, and task workflows, enabling developers to engineer context effectively for their agent products. The platform observes agent tasks and user feedback in real time, offering robust observability into workflows and helping teams understand how agents perform over time. Acontext also... -
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Large Concept Model
Language modeling in a sentence representation space
...It organizes training around concepts (rather than just raw labels), encouraging models to understand attributes, relations, and compositional structure that transfer across tasks. The repository provides training loops, data tooling, and evaluation routines to learn and probe these concept embeddings, typically from large image–text or weakly supervised corpora. It includes utilities to build concept vocabularies, map supervision signals to those vocabularies, and measure zero-shot or few-shot generalization. Probing tools help diagnose what the model knows—e.g., attribute recognition, relation understanding, or compositionality—so you can iterate on data and objectives. ... -
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Super Tiny Icons
Super Tiny Icons are miniscule SVG versions of your favourite website
...Designers and developers can embed the icons directly, recolor them via CSS, or combine them in sprites without raster assets. The repository maintains consistent viewboxes and alignment so icons sit neatly alongside text and other UI elements. It is especially useful for landing pages, status banners, and mobile experiences where every byte matters. -
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Universal Tool Calling Protocol (UTCP)
Official python implementation of UTCP. UTCP is an open standard
The python-utcp repository is the official Python SDK implementation of the Universal Tool Calling Protocol (UTCP). UTCP is an open, modern standard designed to let AI agents call any tool or API directly—over HTTP, CLI, WebSocket, gRPC, and more—without the overhead of extra wrapper layers or middleware. It leverages a modular, plugin-based architecture built around Pydantic models and separates the core functionality into a lightweight client and extensible protocol plugins, enabling... -
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LLM Foundry
LLM training code for MosaicML foundation models
Introducing MPT-7B, the first entry in our MosaicML Foundation Series. MPT-7B is a transformer trained from scratch on 1T tokens of text and code. It is open source, available for commercial use, and matches the quality of LLaMA-7B. MPT-7B was trained on the MosaicML platform in 9.5 days with zero human intervention at a cost of ~$200k. Large language models (LLMs) are changing the world, but for those outside well-resourced industry labs, it can be extremely difficult to train and deploy these models. ... -
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Diffusers
State-of-the-art diffusion models for image and audio generation
Diffusers is the go-to library for state-of-the-art pretrained diffusion models for generating images, audio, and even 3D structures of molecules. Whether you're looking for a simple inference solution or training your own diffusion models, Diffusers is a modular toolbox that supports both. Our library is designed with a focus on usability over performance, simple over easy, and customizability over abstractions. State-of-the-art diffusion pipelines that can be run in inference with just a... -
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spacy-transformers
Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy
spaCy supports a number of transfer and multi-task learning workflows that can often help improve your pipeline’s efficiency or accuracy. Transfer learning refers to techniques such as word vector tables and language model pretraining. These techniques can be used to import knowledge from raw text into your pipeline, so that your models are able to generalize better from your annotated examples. You can convert word vectors from popular tools like FastText and Gensim, or you can load in any pre trained transformer model if you install spacy-transformers. You can also do your own language model pretraining via the spacy pre train command. ... -
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Key-book
Proofs, cases, concept supplements, and reference explanations
The book "Introduction to Machine Learning Theory" (hereinafter referred to as "Introduction") written by Zhou Zhihua, Wang Wei, Gao Wei, and other teachers fills the regret of the lack of introductory works on machine learning theory in China. This book attempts to provide an introductory guide for readers interested in learning machine learning theory and researching machine learning theory in an easy-to-understand language. "Guide" mainly covers seven parts, corresponding to seven... -
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Weights and Biases
Tool for visualizing and tracking your machine learning experiments
...Quickly identify model regressions. Use W&B to visualize results in real time, all in a central dashboard. Focus on the interesting ML. Spend less time manually tracking results in spreadsheets and text files. Capture dataset versions with W&B Artifacts to identify how changing data affects your resulting models. Reproduce any model, with saved code, hyperparameters, launch commands, input data, and resulting model weights. Set wandb.config once at the beginning of your script to save your hyperparameters, input settings (like dataset name or model type), and any other independent variables for your experiments. ... -
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Controllable-RAG-Agent
This repository provides an advanced RAG
...Instead of relying solely on simple semantic search, it builds a deterministic control graph that acts as the “brain” of the agent, orchestrating planning, retrieval, reasoning, and verification across many steps. The pipeline ingests PDFs, splits them into chapters, cleans and preprocesses text, then constructs vector stores for fine-grained chunks, chapter summaries, and book quotes to support nuanced queries. At query time, it anonymizes entities, creates a high-level plan, de-anonymizes and expands that plan into concrete retrieval or reasoning tasks, and executes them in sequence while continuously revising the plan. ... -
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MLJAR Studio
Python package for AutoML on Tabular Data with Feature Engineering
We are working on new way for visual programming. We developed a desktop application called MLJAR Studio. It is a notebook-based development environment with interactive code recipes and a managed Python environment. All running locally on your machine. We are waiting for your feedback. The mljar-supervised is an Automated Machine Learning Python package that works with tabular data. It is designed to save time for a data scientist. It abstracts the common way to preprocess the data,...
