Search Results for "training"
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Showing 28 open source projects for "training"
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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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$300 Free Credits to Build on Google CloudPut your $300 in credit toward real workloads, then keep building with free monthly usage for 20+ products. No commitment and no charge until you upgrade.
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LLM Datasets
Curated list of datasets and tools for post-training
...The repository aims to make datasets easy to inspect and transform, with scripts for downloading, deduping, cleaning, and converting to formats like JSONL that slot into training pipelines. It highlights instruction-tuning and conversation-style corpora while also pointing to code, math, or domain-specific sets for targeted capabilities. Quality is a recurring theme: examples and utilities help filter low-value samples, enforce length limits, and split train/validation consistently so results are comparable. ... -
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ShoppingAgent
Custom Chinese chatbot with Seq2Seq, GPT, and agent features
...In addition to core chatbot functionality, the project introduces agent-based capabilities, enabling practical use cases like automated workflows and task-oriented assistants. It also includes support for small language models and local training scripts, making it accessible for users with limited computational resources. ShoppingAgent can be applied to scenarios such as customer service, question answering, and casual conversation. -
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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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The Web MCP
A powerful Model Context Protocol (MCP) server
...It presents search, crawl, navigate, and extraction tools that agents can call directly, replacing brittle scraping prompts with typed operations. The README markets it as a “gateway” to the live web so assistants don’t fall back to stale training data. Bright Data also advertises a getting-started tier with a free monthly allotment, plus options for remote or self-hosted operation depending on governance needs. Ecosystem materials and examples show how it plugs into MCP-capable runtimes and agent frameworks. Overall, the project is aimed at making web intelligence a reliable building block for agent workflows. -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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CML
Continuous Machine Learning | CI/CD for ML
Continuous Machine Learning (CML) is an open-source CLI tool for implementing continuous integration & delivery (CI/CD) with a focus on MLOps. Use it to automate development workflows, including machine provisioning, model training and evaluation, comparing ML experiments across project history, and monitoring changing datasets. CML can help train and evaluate models, and then generate a visual report with results and metrics, automatically on every pull request. -
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Easy DataSet
A powerful tool for creating datasets for LLM fine-tuning
...It supports ingesting domain-specific documents in a wide range of formats — including PDF, Markdown, DOCX, EPUB, and plain text — and can intelligently segment, clean, and structure content into rich datasets tailored for downstream LLM training needs. The system includes automated question-generation capabilities, hierarchical label trees, and answer generation pipelines that use LLM APIs to produce coherent paired data with customizable templates. Beyond dataset creation, Easy-dataset also provides a built-in evaluation system with model testing and blind-test features, helping teams validate model performance using curated test sets. -
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Machine Learning Systems
Introduction to Machine Learning Systems
Machine Learning Systems is an open educational repository that serves as the source and learning stack for the Machine Learning Systems textbook, a project focused on teaching how to engineer AI systems that work reliably in real-world environments. Rather than concentrating only on model training, the material emphasizes the broader discipline of AI engineering, covering efficiency, reliability, deployment, and evaluation across the full lifecycle of intelligent systems. The repository includes textbook content, supporting labs, and companion tools such as TinyTorch to help learners move from theory to hands-on experimentation. ... -
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darwin-skill
Autoresearch-inspired autonomous skill optimization for Claude Code
darwin-skill is an experimental framework designed to automatically improve AI agent “skills” through iterative evaluation and optimization loops inspired by machine learning training processes. Instead of treating prompts or skill definitions as static assets, the system applies a continuous improvement cycle that evaluates performance, proposes changes, tests outcomes, and either retains or reverts modifications. The framework introduces a scoring system across multiple dimensions, enabling quantitative assessment of skill quality and ensuring that only improvements are preserved over time. ... -
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Context7 Platform
Up-to-date code documentation for LLMs and AI code editors
Context7 is a system that aims to inject fresh, version-specific documentation and code snippets into language model prompts, thereby avoiding reliance on outdated training data or hallucinated APIs. It’s designed to integrate with tools that support the Model Context Protocol (MCP), such as Cursor, Windsurf, and other LLM clients. When a user writes a prompt and appends something like “use context7,” the system detects the libraries or frameworks being asked about, fetches the latest docs/snippets from the source repositories, filters and packages relevant context, and injects them into the LLM’s prompt to guide it toward accurate, up-to-date code. ... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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GitMCP
Turn any GitHub repository into an MCP documentation server for AI
...It enables developer-focused AI tools to access up-to-date project documentation and source code so that responses are grounded in real repository content rather than outdated training data. By exposing repository documentation and code through standardized MCP tools, GitMCP helps reduce incorrect or fabricated answers when AI systems assist with coding tasks. It can operate in repository-specific mode, where an AI assistant connects to a particular project, or in a generic mode that allows switching between multiple repositories dynamically. ... -
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dashAI
dashAI: an interactive platform for training, evaluating and deploying
...Visual data preparation, multi-model experiments, XAI explainability, and a plugin-based extensible catalog. The platform guides users through a complete, traceable workflow — data ingestion → visual exploration → preprocessing → model training → evaluation → explainability — without writing a single line of code. Each step is explicit and reversible, keeping the user in control rather than delegating decisions to an opaque pipeline. -
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Chunsong Customer Service
An intelligent customer service system
CSKeFu is a Customer Support System for Enterprises in a high-performance Low-Touch way, open source and free for the world by Chatopera. At Chatopera, we believe that the more you focus on customer service, the better your business/the more you care about your customers, the better income you earn in return. Help enterprises quickly get out-of-the-box free intelligent customer service system to get a customer support system in minutes. Stick to open source and free, business-friendly... -
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gpu_poor
Calculate token/s & GPU memory requirement for any LLM
gpu_poor is an open-source tool designed to help developers determine whether their hardware is capable of running a specific large language model and to estimate the performance they can expect from it. The project focuses on calculating GPU memory requirements and predicted inference speed for different models, hardware configurations, and quantization strategies. By analyzing factors such as model size, context length, batch size, and GPU specifications, the system estimates how much VRAM... -
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Teachable Machine
Explore how machine learning works, live in the browser
...The project is built using web technologies and the TensorFlow.js ecosystem, enabling machine learning models to run locally within the browser environment. Because the training occurs locally, the system can respond quickly to new examples and provide immediate feedback to users. -
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MITRE Annotation Toolkit
A toolkit for managing and manipulating text annotations
...It can be customized for specific tasks (e.g., named entity identification, de-identification of medical records). The goal of MAT is not to help you configure your training engine (in the default case, the Carafe CRF system) to achieve the best possible performance on your data. MAT is for "everything else": all the tools you end up wishing you had. -
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neurojs
A JavaScript deep learning and reinforcement learning library
neurojs is a JavaScript framework designed to enable deep learning and reinforcement learning directly within web environments. The library provides a full machine learning framework implemented in JavaScript that can run inside browsers or Node.js environments. It focuses particularly on reinforcement learning algorithms, enabling developers to create intelligent agents that learn through interaction with simulated environments. The framework supports neural network architectures and... -
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Universal Data Tool
Collaborate & label any type of data, images, text, or documents etc.
...Working together, we can accomplish more. The Universal Data Tool was built to bring together the best ideas from different machine learning communities. Upload your dataset to Courses to create a training course. Testing and exercises validate that your workforce knows exactly how the data should be labeled. Get started in less than a minute. Courses uses administrator links. No sign up needed. -
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Semantic Segmentation Editor
Web labeling tool for bitmap images and point clouds
A web-based labeling tool for creating AI training data sets (2D and 3D). The tool has been developed in the context of autonomous driving research. It supports images (.jpg or .png) and point clouds (.pcd). It is a Meteor app developed with React, Paper.js, and three.js. -
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DCGAN in Tensorflow
Deep Convolutional Generative Adversarial Networks
DCGAN-tensorflow is a classic TensorFlow implementation of Deep Convolutional Generative Adversarial Networks, intended to demonstrate and reproduce the stabilized GAN architecture described in the original research. The repository provides complete training scripts, model definitions, and utilities for generating synthetic images from datasets such as MNIST and CelebA. It serves both as an educational reference and as a practical starting point for developers experimenting with generative models. The implementation includes adjustments such as updating the generator more frequently than the discriminator to help stabilize training. ... -
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NLP.js
An NLP library for building bots
...Natural Language Processing Classifier, to classify an utterance into intents. NLP Manager, a tool able to manage several languages, the Named Entities for each language, the utterances, and intents for the training of the classifier, and for a given utterance return the entity extraction, the intent classification and the sentiment analysis. -
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SQLFlow
SQL compiler bridging databases and machine learning workflows
...By embedding machine learning operations into SQL, it removes the need for users to switch between programming languages such as Python or R, simplifying the overall workflow. SQLFlow also supports model training, prediction, and explanation tasks, allowing data practitioners to work entirely within a familiar query interface. -
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Supervised Reptile
Code for the paper "On First-Order Meta-Learning Algorithms"
...The repo includes training scripts, dataset fetchers (Omniglot, Mini-ImageNet), and modules for defining the Reptile update logic, variables, and hyperparameters. -
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CrypTen
A framework for Privacy Preserving Machine Learning
...The framework supports both encryption and decryption of tensors and operations such as addition and multiplication over encrypted values. Although not yet production-ready, CrypTen focuses on advancing real-world secure ML applications, such as training and inference over private datasets, without exposing sensitive data. -
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Rasa-UI
Rasa UI is a frontend for the Rasa Framework
...Rasa UI provides a web application to quickly and easily be able to create and manage bots, NLU components (Regex, Examples, Entities, Intents, etc.) and Core components (Stories, Actions, Responses, etc.) through a web interface. It also provides some convenience features for Rasa, like training and loading your models, monitoring usage or viewing logs. -
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face-recognition.js
Simple Node.js package for robust face detection and face recognition
face-recognition.js is a Node.js wrapper around dlib’s face detection and recognition tools. It provides JavaScript and TypeScript APIs for loading images, locating faces, extracting face crops, and training labeled recognizers. Developers can compare unknown faces with stored examples and receive ranked predictions with distance values. The package also includes five-point and 68-point facial landmark predictors for alignment and analysis. Synchronous and Promise-based asynchronous methods support different application designs, while OpenCV integration enables additional image processing. ...
