Search Results for "repository" - Page 14
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Showing 1010 open source projects for "repository"
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UCO3D
Uncommon Objects in 3D dataset
...Each sequence also ships with a precomputed 3D Gaussian Splat reconstruction, enabling fast, differentiable rendering workflows and modern implicit/point-based modeling experiments. The repository includes automated downloaders with checksum verification, fine-grained controls to fetch only selected modalities or super-categories, and a lightweight Python API for loading frames, geometry, and splats on demand. Metadata is indexed in SQLite for quick queries at scale, and helper builders handle alignment, undistortion, frame extraction from videos, and cropping around the object. -
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GLM-4-Voice
GLM-4-Voice | End-to-End Chinese-English Conversational Model
...GLM-4-Voice builds upon the bilingual strengths of the GLM architecture, supporting both Chinese and English, and is designed to handle long-form conversations with context retention. The repository provides model weights, inference demos, and setup instructions for deploying speech-enabled AI systems. -
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Super-Linter
Combination of multiple linters to install as a GitHub Action
This repository is for the GitHub Action to run a Super-Linter. It is a simple combination of various linters, written in bash, to help validate your source code. The super-linter finds issues and reports them to the console output. Fixes are suggested in the console output but not automatically fixed, and a status check will show up as failed on the pull request. -
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Cha
Deprecated AI CLI for terminal based interactions
Cha is a command-line AI assistant for terminal-based interaction with large language models. It was designed to let developers chat with AI from the terminal while keeping control over the workflow and environment. The repository now serves as a historical reference because active development moved to Ch, a faster Go-based successor. Cha included support materials such as optional search setup assets, including SearXNG-related configuration instructions. Its value today is mostly archival, showing the earlier implementation and design direction that led to Ch. ... -
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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Comprehensive Python Cheatsheet
Comprehensive Python Cheatsheet
...It covers a broad range of topics including data structures, control flow, functions, object-oriented programming, standard library usage, and common patterns. The repository includes both web and printable versions, allowing users to access the material in multiple formats depending on their workflow. Because it is continuously maintained, the cheatsheet reflects modern Python usage and practical conventions. Overall, it serves as a fast lookup companion for everyday Python development. -
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Claude Quickstarts
A collection of projects for building deployable applications
...Each quickstart provides a foundational codebase with preconfigured settings and examples for common deployment scenarios, so developers can focus on customizing functionality instead of bootstrapping infrastructure. The repository includes demos, sample integrations, and instructions to get environments running with minimal setup while handling authentication, API calls, and error handling best practices. Because it’s designed as a learning and prototyping resource, Claude Quickstarts supports exploration of interactive applications, backend services, and workflows that benefit from large language model capabilities. -
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Adapters
A Unified Library for Parameter-Efficient Learning
Adapters is an add-on library to HuggingFace's Transformers, integrating 10+ adapter methods into 20+ state-of-the-art Transformer models with minimal coding overhead for training and inference. Adapters provide a unified interface for efficient fine-tuning and modular transfer learning, supporting a myriad of features like full-precision or quantized training (e.g. Q-LoRA, Q-Bottleneck Adapters, or Q-PrefixTuning), adapter merging via task arithmetics or the composition of multiple adapters... -
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OpenClaw Medical Skills
The largest open-source medical AI skills library for OpenClaw
...Each skill is packaged as a modular component that can be integrated into an OpenClaw-based AI assistant, allowing the agent to perform expert-level reasoning and workflows in medical contexts. Instead of relying on general-purpose language model responses, the repository equips AI agents with structured instructions and tools tailored to medical knowledge and datasets. This modular design allows developers and researchers to build AI systems that can access specialized medical reasoning processes, retrieve relevant biomedical information, and generate structured outputs suitable for analysis or downstream processing. -
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vim-ai
AI-powered code assistant for Vim. OpenAI and ChatGPT plugin for Vim
...Its command set covers text completion, editing, chat continuation, image generation, and debugging utilities, making it more versatile than a narrow autocomplete add-on. The repository also highlights support for custom roles, vision features such as image-to-text, and an emerging provider-plugin model for extending compatibility further. A notable design point is that it only sends content the user explicitly selects or includes in prompts, which helps users control what is shared with the external model. -
Your monitoring isn't a stack. It's a pile. Fix that.Replace Datadog, New Relic, and Sentry without adding three more dashboards.
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llms-from-scratch-cn
Build a large language model from 0 only with Python foundation
llms-from-scratch-cn is an educational open-source project designed to teach developers how to build large language models step by step using practical code and conceptual explanations. The repository provides a hands-on learning path that begins with the fundamentals of natural language processing and gradually progresses toward implementing full GPT-style architectures from the ground up. Rather than focusing on using pre-trained models through APIs, the project emphasizes understanding the internal mechanisms of modern language models, including tokenization, attention mechanisms, transformer architecture, and training workflows. ... -
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Oasis
Inference script for Oasis 500M
...The project focuses on enabling action-conditional frame generation so developers can experiment with interactive, model-generated environments rather than static video generation alone. Because it’s an inference-focused repository, it’s especially useful as a practical reference for running the model, wiring inputs, and producing the autoregressive sequence of gameplay frames. It also serves as a research sandbox for people exploring how far interactive generative models can go with smaller, more accessible checkpoints compared to massive internal systems. -
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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. Its north star is approachability and speed: you can boot a fresh GPU box and drive the whole pipeline via a single script, producing a usable chat model in hours and a clear markdown report of what happened. ... -
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Courses (Anthropic)
Anthropic's educational courses
Anthropic’s courses repository is a growing collection of self-paced learning materials that teach practical AI skills using Claude and the Anthropic API. It’s organized as a sequence of hands-on courses—starting with API fundamentals and prompt engineering—so learners build capability step by step rather than in isolation. Each course mixes short readings with runnable notebooks and exercises, guiding you through concepts like model parameters, streaming, multimodal prompts, structured outputs, and evaluation. ... -
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nanoGPT
The simplest, fastest repository for training/finetuning models
NanoGPT is a minimalistic yet powerful reimplementation of GPT-style transformers created by Andrej Karpathy for educational and research use. It distills the GPT architecture into a few hundred lines of Python code, making it far easier to understand than large, production-scale implementations. The repo is organized with a training pipeline (dataset preprocessing, model definition, optimizer, training loop) and inference script so you can train a small GPT on text datasets like Shakespeare... -
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The Missing Semester
The Missing Semester of Your CS Education
The Missing Semester is a course and repository that teaches the engineering skills often skipped in traditional computer science curricula: command-line fluency, shell scripting, editors, version control, debugging, data wrangling, and automation. It includes lecture notes, exercises, and sample solutions that encourage hands-on practice rather than passive reading. The curriculum demystifies tools like bash, vim, git, and make, showing how to combine them into efficient workflows that scale from homework to production systems. ... -
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shuyuan
Reading book source
...The name suggests “academy” or “study hall,” and the tool aims to help users ingest, organize, and manage reading content — possibly offering features like text parsing, annotation, metadata generation, translation, or storage for later reference. The repository is set up to support document ingestion, indexing, and maybe some AI-aided summarization or lookup functions, which helps users convert large text corpora into a structured, searchable knowledge base. For learners, researchers, or avid readers, Shuyuan offers a way to bridge from plain text files or eBooks into a manageable, interactive resource — one where notes, references, and reading progress can be tracked. ... -
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Code-Mode
Plug-and-play library to enable agents to call MCP and UTCP tools
...This approach can dramatically reduce the number of tool-call iterations needed in complex workflows, turning multi-step call chains into a single code execution with internal branching and loops. The repository contains both TypeScript and Python libraries, plus a code-mode-mcp component for integrating with MCP and UTCP ecosystems. Benchmarks in the README highlight improvements in latency and token cost for scenarios involving multiple tools, showing that code execution often outperforms traditional JSON-based function calling. -
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Real-Time Voice Cloning
Clone a voice in 5 seconds to generate arbitrary speech in real-time
Real-Time Voice Cloning is an influential deep-learning repository that demonstrates how to clone a voice from just a few seconds of audio and then generate arbitrary speech in that voice in near real time. It implements the SV2TTS pipeline (“Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis”) in three stages: a speaker encoder, a synthesizer, and a vocoder. -
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jlens
Companion code for the global workspace interpretability paper
...Interactive layer-by-position views reveal how token rankings evolve across the network and compare them with the model’s final output. It supports open-weight Hugging Face decoder models, with Qwen used in the included examples. The repository also provides synthetic evaluation data and an end-to-end notebook, but it is not maintained. -
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ThinkStats2
Text and supporting code for Think Stats, 2nd Edition
...Case studies draw from public sources, including health-related datasets, to connect abstract concepts with realistic analysis. Each chapter has a notebook containing examples and exercises, along with a separate version that includes solutions. The repository also provides reusable thinkstats2 and thinkplot packages, homework material, workshops, and book-building files. Learners can use the notebooks in Google Colab or download the project for local work. -
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HRM-Text
1B text generation model based on the HRM architecture
...The system combines hierarchical recurrent design, task-completion strengthening, and latent-space reasoning. Its training stack includes PrefixLM sequence packing, FlashAttention 3 kernels, PyTorch FSDP2, evaluation scripts, and checkpoint conversion tools. The repository supports reference pretraining runs for smaller and larger configurations, with Hopper-class GPUs expected for the attention path. It is useful for researchers and engineers exploring efficient language model pretraining, reasoning-focused architectures, and reproducible foundation model experiments. -
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Train LLM From Scratch
A straightforward method for training your LLM
...It is based on the architecture described in Attention Is All You Need and is designed to make the training pipeline understandable rather than hidden behind a large framework. The repository walks through the process from downloading data to generating text with a trained model. It supports training smaller or larger models, including million- and billion-parameter configurations depending on available hardware. A major goal is accessibility, since the author frames it as possible to train models using a single GPU. ... -
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Claude for Legal
A suite of plugins for legal workflows
...Its workflows include contract review, NDA triage, diligence review, DSAR response, employment policy drafting, trademark screening, regulatory monitoring, and litigation support. The repository emphasizes attorney oversight, source attribution, jurisdiction awareness, conservative legal assumptions, and approval gates before anything is filed, sent, or relied on. -
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NVIDIA AI Blueprint
Suite of reference architectures for building GPU-accelerated vision
...It is designed for technical users who need deployable reference architectures for smart spaces, warehouse automation, SOP validation, monitoring, and operational video analytics. The repository includes Python agent code, Docker Compose deployment configurations, skills, scripts, and a Next.js-based UI. -
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AI-DLC
AI-Driven Life Cycle (AI-DLC) adaptive workflow steering rules for AI
...Rather than focusing on a single model or IDE, the framework provides reusable rules, templates, and orchestration patterns compatible with tools such as Amazon Q Developer, Claude Code, Cursor, GitHub Copilot, and Cline. The repository emphasizes reproducible development processes, workflow portability, and AI-guided engineering discipline across different environments. It also explores specification-driven development and layered workflow architectures that standardize how AI systems interact with software projects.