Search Results for "model-builder" - Page 87

Showing 7002 open source projects for "model-builder"

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  • 1
    WavTokenizer

    WavTokenizer

    SOTA discrete acoustic codec models with 40/75 tokens per second

    ...It is built to represent speech, music, and general audio with extremely low bitrate, making it ideal as a front-end for large audio language models like GPT-4o and similar architectures. The model uses a single-quantizer design together with temporal compression to achieve extreme compression without sacrificing reconstruction fidelity. Its architecture incorporates a broader vector-quantization space, extended contextual windows, and improved attention networks, combined with multi-scale discriminators and inverse Fourier transform blocks to enhance waveform reconstruction. ...
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  • 2
    Libros de Programación en Español

    Libros de Programación en Español

    List of programming books in Spanish for free

    Libros de Programación en Español is a curated list of free programming books in Spanish, organized by topic and technology so learners can find high-quality materials without cost. The README is structured as an index with general programming books, followed by sections for specific languages such as JavaScript, TypeScript, Python, Ruby, Rust, PHP, Haskell, Go, Kotlin, Java, and R.Each entry includes the book title, author, and a link to the official or legal free version (PDF, HTML, eBook,...
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  • 3
    Blik

    Blik

    Self hosted & open source anonymous 360 review software

    Blik is an open source, self-hosted platform for anonymous 360-degree feedback and performance review cycles, built with a strong focus on privacy, transparency, and developer-friendly deployment. It allows organizations to run review cycles where employees get anonymous feedback from peers, managers, and direct reports, without vendor lock-in or per-user licensing costs. The system is built using the Django framework, with a PostgreSQL backend, and is packaged for easy deployment via...
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  • 4
    Prompt Engineering Techniques

    Prompt Engineering Techniques

    Collection of tutorials for Prompt Engineering techniques

    ...It contains around twenty-plus hands-on Jupyter notebooks, each dedicated to a specific technique such as basic prompt structures, prompt templates and variables, zero-shot prompting, few-shot prompting, chain-of-thought, self-consistency, constrained generation, role prompting, task decomposition, and more. The tutorials are designed to be practical; you can run them directly, examine the prompts, and see how small changes affect model behavior and quality. The repository is framed as a “techniques library” that complements a more detailed book, which expands on the same topics with deeper explanations and exercises. It is intended for a wide audience, from beginners learning how to structure their first prompts to advanced practitioners optimizing stability, controllability, and reliability in production systems.
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    Agents Towards Production

    Agents Towards Production

    Code-first tutorials covering every layer of GenAI agents

    ...These tutorials show how to implement things like secure tool calling with OAuth, dual-memory architectures, production RAG agents, multi-agent communication protocols, GPU deployment, containerization with Docker, FastAPI endpoints, and Streamlit chat UIs. The architecture diagram and accompanying material provide a mental model for how production-grade agents should be wired together.
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  • 6
    LLM Course

    LLM Course

    Course to get into Large Language Models (LLMs)

    ...Evaluation is treated as a first-class topic, with examples of automatic and human-in-the-loop methods to catch regressions and verify quality beyond simple loss values. By the end, students have a mental model and a practical toolkit for iterating on datasets, training configs, etc.
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  • 7
    windsurf.vim

    windsurf.vim

    Free, ultrafast Copilot alternative for Vim and Neovim

    ...The plugin supports major programming languages and allows you to trigger completions as you type—especially after comments or partial code constructs. Because it is designed to integrate with Vim’s editing model, it offers suggestions in-line and leverages virtual text or inline indicators when supported. Many developers using Neovim look to this plugin as a way to bring modern AI-powered code-assistance into their terminal-centric workflow.
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  • 8
    Schema.DTS

    Schema.DTS

    JSON-LD TypeScript types for Schema vocabulary

    The project provides a comprehensive set of TypeScript typings based on the Schema vocabulary, enabling developers to author JSON-LD structured data with strong type safety. It supplies both high-level discriminated unions and helper types to model contexts, graphs, and linked data relationships with clarity and accuracy. Usage examples demonstrate how one can import types like Person, WithContext, or Graph and compose JSON-LD objects in a way that aligns with semantic-web and knowledge-graph practices. The repository also contains a generator tool that can pull ontology definitions and emit TypeScript definitions in bulk, ensuring the typings stay up to date and maintain consistency. ...
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  • 9
    Tracking Any Point (TAP)

    Tracking Any Point (TAP)

    DeepMind model for tracking arbitrary points across videos & robotics

    TAPNet is the official Google DeepMind repository for Tracking Any Point (TAP), bundling datasets, models, benchmarks, and demos for precise point tracking in videos. The project includes the TAP-Vid and TAPVid-3D benchmarks, which evaluate long-range tracking of arbitrary points in 2D and 3D across diverse real and synthetic videos. Its flagship models—TAPIR, BootsTAPIR, and the latest TAPNext—use matching plus temporal refinement or next-token style propagation to achieve state-of-the-art...
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  • 10
    vJEPA-2

    vJEPA-2

    PyTorch code and models for VJEPA2 self-supervised learning from video

    ...Instead of reconstructing pixels, it predicts the missing high-level embeddings of masked space-time regions using a context encoder and a slowly updated target encoder. This objective encourages the model to learn semantics, motion, and long-range structure without the shortcuts that pixel-level losses can invite. The architecture is designed to scale: spatiotemporal ViT backbones, flexible masking schedules, and efficient sampling let it train on long clips while remaining stable. Trained representations transfer well to downstream tasks such as action recognition, temporal localization, and video retrieval, often with simple linear probes or light fine-tuning. ...
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  • 11
    OpenAI .NET

    OpenAI .NET

    The official .NET library for the OpenAI API

    OpenAI .NET is the official client library for calling the OpenAI REST API from C# and other .NET languages, with first-class support for modern .NET patterns. It provides strongly typed clients across API areas (chat, audio, images, embeddings, moderations, batches, files, models, vector stores, responses, realtime, assistants) and works with .NET Standard 2.0 while the examples use .NET 8. You install it via NuGet and authenticate with an API key, ideally through environment variables or...
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  • 12
    FlashMLA

    FlashMLA

    FlashMLA: Efficient Multi-head Latent Attention Kernels

    FlashMLA is a high-performance decoding kernel library designed especially for Multi-Head Latent Attention (MLA) workloads, targeting NVIDIA Hopper GPU architectures. It provides optimized kernels for MLA decoding, including support for variable-length sequences, helping reduce latency and increase throughput in model inference systems using that attention style. The library supports both BF16 and FP16 data types, and includes a paged KV cache implementation with a block size of 64 to efficiently manage memory during decoding. On very compute-bound settings, it can reach up to ~660 TFLOPS on H800 SXM5 hardware, while in memory-bound configurations it can push memory throughput to ~3000 GB/s. ...
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  • 13
    Kaldi

    Kaldi

    kaldi-asr/kaldi is the official location of the Kaldi project

    Kaldi is an open source toolkit for speech recognition research. It provides a powerful framework for building state-of-the-art automatic speech recognition (ASR) systems, with support for deep neural networks, Gaussian mixture models, hidden Markov models, and other advanced techniques. The toolkit is widely used in both academia and industry due to its flexibility, extensibility, and strong community support. Kaldi is designed for researchers who need a highly customizable environment to...
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  • 14
    OpenAI Realtime Agents

    OpenAI Realtime Agents

    This is a simple demonstration of more advanced, agentic patterns

    ...It also supports a “Chat-Supervisor” pattern where a lightweight realtime chat agent handles user interactions and delegates more complex reasoning or tool usage to a stronger textual model (e.g. GPT-4). Because realtime agents are still a beta feature, the code and API surface are subject to changes and may evolve.
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  • 15
    Tomb

    Tomb

    the Crypto Undertaker

    ...Permissions and ownership hygiene are emphasized to avoid leaking metadata, and the tool favors auditable shell operations that experienced users can inspect. Tomb’s model suits people who want encrypted containers with Unix-friendly ergonomics, keeping secrets safe while integrating cleanly into everyday scripts and workflows.
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  • 16
    Scalaz

    Scalaz

    Principled Functional Programming in Scala

    ...It implements classic abstractions such as Functor, Applicative, Monad, Monoid, Foldable, and Traverse, along with powerful transformers (ReaderT, StateT, WriterT, OptionT, and more) to structure effects. The library offers rich data structures—\/ (disjunction), Validation, NonEmptyList, IList, and Free—that help model errors, invariants, and interpretable programs. Its type class–oriented design lets you write generic algorithms over capabilities rather than concrete types, improving reuse and testability. Scalaz also contributes optics, equality/ordering abstractions, and lawful instances with property-based tests to ensure algebraic laws hold. ...
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  • 17
    Searchkick

    Searchkick

    Intelligent search made easy

    Searchkick brings powerful, production-ready search to Rails by mapping Active Record models into Elasticsearch with sensible defaults and easy customization. It supports language analyzers, stemming, synonyms, misspelling tolerance, and highlighting so search results feel natural to end users. Indexing is model-centric: you declare what fields to index, add computed fields, and trigger reindexing via callbacks or background jobs, with options for zero-downtime rolling reindexes. On the query side, a simple API covers relevance tuning, boosting, filtering, faceting/aggregations, and pagination, while still allowing direct access to advanced Elasticsearch features when needed. ...
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  • 18
    Koa

    Koa

    Expressive middleware for node.js using ES2017 async functions

    Koa is a minimal, expressive web framework for Node.js created by the team behind Express, built around modern JavaScript features. Its middleware system uses async functions and an “onion” execution model, producing clean, sequential control flow for request/response handling. Koa keeps the core small and unopinionated—there’s no built-in router or templating—so developers compose only the pieces they need. The framework exposes a refined Context object to standardize request and response utilities without obscuring Node’s primitives. ...
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  • 19
    Apache Seata

    Apache Seata

    High-performance, open source distributed transaction solution

    Seata is a distributed transaction solution for microservices that provides consistent, cross-service commits without forcing every team to adopt the same persistence model. Its architecture separates responsibilities into a global coordinator and per-service participants, so business services remain decoupled while transactions are orchestrated centrally. Multiple modes are supported—AT (automatic, SQL-based with undo logs), TCC (try-confirm-cancel), Saga (long-running compensation), and XA—letting architects choose between simplicity, control, and interoperability. ...
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  • 20
    Live Svelte

    Live Svelte

    Svelte inside Phoenix LiveView with seamless end-to-end reactivity

    ...This makes it straightforward to adopt Svelte for isolated, highly interactive widgets—charts, editors, complex form controls—without abandoning LiveView’s real-time model. The project aims to keep build tooling minimal and predictable, so teams can continue using familiar Phoenix asset pipelines. By enabling “islands” of Svelte within LiveView pages, live_svelte offers a pragmatic path to richer UX while preserving Elixir’s server-centric simplicity.
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  • 21
    LLM Foundry

    LLM Foundry

    LLM training code for MosaicML foundation models

    ...This has led to a flurry of activity centered on open-source LLMs, such as the LLaMA series from Meta, the Pythia series from EleutherAI, the StableLM series from StabilityAI, and the OpenLLaMA model from Berkeley AI Research.
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  • 22
    GPTel

    GPTel

    A no-frills ChatGPT client for Emacs

    ...It will ask you for the key if you skipped the previous step. Run it with a prefix-arg to start a new session. In the gptel buffer, send your prompt with M-x gptel-send, bound to C-c RET. Set chat parameters (GPT model, directives etc) for the session by calling gptel-send with a prefix argument.
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  • 23
    NVIDIA FLARE

    NVIDIA FLARE

    NVIDIA Federated Learning Application Runtime Environment

    NVIDIA Federated Learning Application Runtime Environment NVIDIA FLARE is a domain-agnostic, open-source, extensible SDK that allows researchers and data scientists to adapt existing ML/DL workflows(PyTorch, TensorFlow, Scikit-learn, XGBoost etc.) to a federated paradigm. It enables platform developers to build a secure, privacy-preserving offering for a distributed multi-party collaboration. NVIDIA FLARE is built on a componentized architecture that allows you to take federated...
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  • 24
    Deep Lake

    Deep Lake

    Data Lake for Deep Learning. Build, manage, and query datasets

    ...Use one API to upload, download, and stream datasets to/from AWS S3/S3-compatible storage, GCP, Activeloop cloud, or local storage. Store images, audios and videos in their native compression. Deeplake automatically decompresses them to raw data only when needed, e.g., when training a model. Treat your cloud datasets as if they are a collection of NumPy arrays in your system's memory. Slice them, index them, or iterate through them.
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  • 25
    Argo Workflows

    Argo Workflows

    Workflow engine for Kubernetes

    Argo Workflows is an open source container-native workflow engine for orchestrating parallel jobs on Kubernetes. Argo Workflows is implemented as a Kubernetes CRD (Custom Resource Definition). Define workflows where each step in the workflow is a container. Model multi-step workflows as a sequence of tasks or capture the dependencies between tasks using a directed acyclic graph (DAG). Easily run compute intensive jobs for machine learning or data processing in a fraction of the time using Argo Workflows on Kubernetes. Run CI/CD pipelines natively on Kubernetes without configuring complex software development products. ...
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