Search Results for "dynamicreports-examples" - Page 3
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Showing 659 open source projects for "dynamicreports-examples"
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POT
Python Optimal Transport
This open source Python library provides several solvers for optimization problems related to Optimal Transport for signal, image processing and machine learning. -
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Implicit
Fast Python collaborative filtering for implicit feedback datasets
This project provides fast Python implementations of several different popular recommendation algorithms for implicit feedback datasets. All models have multi-threaded training routines, using Cython and OpenMP to fit the models in parallel among all available CPU cores. In addition, the ALS and BPR models both have custom CUDA kernels - enabling fitting on compatible GPU’s. This library also supports using approximate nearest neighbour libraries such as Annoy, NMSLIB and Faiss for speeding... -
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Agently 4
Build GenAI application quick and easy
...It abstracts away boilerplate around model API calls, tool usage, prompt management, and workflow state. The project aims at production-grade GenAI application development rather than just one-off scripts — you’ll find examples of news gathering, agentic workflows, control systems, etc. It is licensed under Apache-2.0, allowing commercial use and modification. Because it's built in Python, it integrates easily with existing data pipelines, databases, and agent architectures. -
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Prompt in-context learning
Resources for in-context learning and prompt engineering
Prompt-In-Context-Learning is an open-source repository that serves as a comprehensive engineering guide and curated resource collection for understanding and applying in-context learning and prompt engineering with large language models. The project gathers research papers, tutorials, prompt examples, and practical guides that help developers and researchers learn how to design effective prompts for models such as GPT-3, ChatGPT, and other foundation models. In-context learning refers to the ability of language models to learn a task directly from examples provided in the prompt without updating the model’s parameters, allowing them to perform new tasks through demonstration alone. ... -
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CV-CUDA
CV-CUDA™ is an open-source, GPU accelerated library
CV-CUDA is an open-source project that enables building efficient cloud-scale Artificial Intelligence (AI) imaging and computer vision (CV) applications. It uses graphics processing unit (GPU) acceleration to help developers build highly efficient pre- and post-processing pipelines. CV-CUDA originated as a collaborative effort between NVIDIA and ByteDance. -
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Academic Research Skills for Claude Code
Academic Research Skills for Claude Code
...The project is designed as a self-guided resource, helping learners understand how to evaluate sources, synthesize information, and develop strong arguments. It likely integrates examples, templates, and conceptual explanations to bridge the gap between theory and practical research execution. The repository emphasizes skill-building rather than automation, making it especially useful for students and early-career researchers. Its overall goal is to enhance research literacy and reproducibility in academic workflows. -
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Turing.jl
Bayesian inference with probabilistic programming
Bayesian inference with probabilistic programming. -
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GPT Computer Assistant
gpt-4o for windows, macos and linux
This is an alternative work for providing ChatGPT MacOS app to Windows and Linux. In this way, this is a fresh and stable work. You can easily install as a Python library for this time but we will prepare a pipeline for providing native install scripts (.exe). -
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MLX-Audio
A text-to-speech, speech-to-text and speech-to-speech library
...The project provides a straightforward CLI (mlx_audio.tts.generate) as well as a Python API for programmatic generation of audio, including parameters for voice choice, speed, language hints, output format, and sample rate. It includes examples such as audiobook generation to demonstrate long-form synthesis and joined audio segments. On top of that, MLX-Audio offers a modern web interface powered by FastAPI, with real-time waveform and 3D visualizations, file upload, and audio management. -
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Granite TSFM
Foundation Models for Time Series
...The repository focuses on end-to-end workflows: loading data, building datasets, fine-tuning forecasters, running evaluations, and serving models. It documents the currently supported Python versions and points users to where the core TSFM models are hosted and how to wire up service components. Issues and examples in the tracker illustrate common tasks such as slicing inference windows or using pipeline helpers that return pandas DataFrames, grounding the library in day-to-day time-series operations. The ecosystem around TSFM also includes a community cookbook of “recipes” that showcase capabilities and patterns. Overall, the repo is designed as a hands-on companion for teams adopting time-series foundation models in production-leaning settings. -
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SpeechRecognition
Speech recognition module for Python
Library for performing speech recognition, with support for several engines and APIs, online and offline. Recognize speech input from the microphone, transcribe an audio file, save audio data to an audio file. Show extended recognition results, calibrate the recognizer energy threshold for ambient noise levels (see recognizer_instance.energy_threshold for details). Listening to a microphone in the background, various other useful recognizer features. The easiest way to install this is using... -
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how-to-optim-algorithm-in-cuda
How to optimize some algorithm in cuda
...These examples show how different optimization techniques influence performance on modern GPU hardware and allow readers to experiment with real implementations. The repository also contains extensive learning notes that summarize CUDA programming concepts, GPU architecture details, and performance engineering strategies. -
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llmx.txt hub
The largest directory for AI-ready documentation and tools
...The repository aims to standardize patterns for allowlists, denylists, attribution, rate expectations, and contact information, mirroring the spirit of robots.txt for the AI era. It provides examples and templates to make adoption straightforward for maintainers of websites, docs portals, and repos. The hub encourages community debate and iteration so conventions remain practical as tooling evolves. By consolidating examples and tools, it accelerates consistent, respectful AI consumption of public content. -
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Milvus Bootcamp
Dealing with all unstructured data, such as reverse image search
Milvus Bootcamp is a collection of tutorials, examples, and best practices for using Milvus, an open-source vector database designed for AI-powered similarity search and retrieval applications. -
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supabase-py
Python Client for Supabase. Query Postgres from Flask, Django
Python Client for Supabase. Query Postgres from Flask, Django, FastAPI. Python user authentication, security policies, edge functions, file storage, and realtime data streaming. Good first issue. -
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Evaluate
A library for easily evaluating machine learning models and datasets
Evaluate is a library that makes evaluating and comparing models and reporting their performance easier and more standardized. -
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LangCheck
Simple, Pythonic building blocks to evaluate LLM applications
Simple, Pythonic building blocks to evaluate LLM applications. -
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Bespoke Curator
Synthetic data curation for post-training and data extraction
...The system helps developers generate, transform, and curate high-quality datasets by combining automated generation with structured validation and filtering. It supports workflows where models are used to produce synthetic examples that can later be refined into reliable training datasets for reasoning, question answering, or structured information extraction tasks. Curator includes tools for monitoring data generation processes and managing dataset quality while large batches of examples are being created. The framework also integrates with multiple inference systems and APIs, allowing users to generate data using different model providers or open-source inference engines. -
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Magika
Fast and accurate AI powered file content types detection
...It also emphasizes reproducibility and developer ergonomics with clear install and usage instructions for common platforms. A public site complements the repo with background, examples, and guidance for integrating Magika into existing workflows. -
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Anthropic SDK TypeScript
Access to Anthropic's safety-first language model APIs
...It supports streaming endpoints as well. Because TypeScript provides type safety, it helps avoid common errors in JSON interplay. The repo also includes documentation (API spec in api.md) and examples (e.g. streaming examples). -
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avante.nvim
Use your Neovim like using Cursor AI IDE!
avante.nvim is a Neovim plugin designed to emulate the behaviour of the Cursor AI IDE. It provides users with AI-driven code suggestions and the ability to apply these recommendations directly to their source files with minimal effort. -
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Laminar
Open-source all-in-one platform for engineering AI products
...When you trace your LLM application, you get a clear picture of every step of execution and simultaneously collect invaluable data. You can use it to set up better evaluations, as dynamic few-shot examples, and for fine-tuning. All traces are sent in the background via gRPC with minimal overhead. Tracing of text and image models is supported, audio models are coming soon. You can set up LLM-as-a-judge or Python script evaluators to run on each received span. Evaluators label spans, which is more scalable than human labeling, and especially helpful for smaller teams. ... -
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Telegram for GitHub Actions
GitHub Action that sends a Telegram message.
GitHub Action for sending a Telegram notification message. -
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FLUX.1
Official inference repo for FLUX.1 models
...The project is part of a larger family of FLUX models developed by Black Forest Labs, designed to produce high-quality, detailed visuals from text descriptions with competitive prompt adherence and artistic fidelity. This repo focuses on running the open-source model variants efficiently, providing scripts, model loading logic, and examples for local installations, and supports integration with Python toolchains like PyTorch and popular generative pipelines. Users can launch CLI tools to generate images, experiment with different FLUX variants, and extend the base code for research-oriented applications. -
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xiaohongshu-mcp
MCP for xiaohongshu.com
xiaohongshu-mcp is a Model Context Protocol (MCP) server that equips AI assistants with first-class tools for working on Xiaohongshu (Little Red Book), focusing on day-to-day creator and operator workflows rather than generic browsing. The project centers on authenticated actions and data access that matter to content operations, such as checking login state, publishing or scheduling content, fetching recommendations and search results, reading post details, and acting on comments. It’s...
