Search Results for "can" - Page 53
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Showing 5017 open source projects for "can"
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Optopsy
A nimble options backtesting library for Python
Optopsy is a Python-based, nimble backtesting and statistics library focused on evaluating options trading strategies like calls, puts, straddles, spreads, and more, using pandas-driven analysis. The csv_data() function is a convenience function. Under the hood it uses Panda's read_csv() function to do the import. There are other parameters that can help with loading the csv data, consult the code/future documentation to see how to use them. Optopsy is a small simple library that offloads the heavy work of backtesting option strategies, the API is designed to be simple and easy to implement into your regular Panda's data analysis workflow. As such, we just need to call the long_calls() function to have Optopsy generate all combinations of a simple long call strategy for the specified time period and return a DataFrame. ... -
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NVIDIA NeMo
Toolkit for conversational AI
...NeMo has separate collections for Automatic Speech Recognition (ASR), Natural Language Processing (NLP), and Text-to-Speech (TTS) models. Each collection consists of prebuilt modules that include everything needed to train on your data. Every module can easily be customized, extended, and composed to create new conversational AI model architectures. Conversational AI architectures are typically large and require a lot of data and compute for training. NeMo uses PyTorch Lightning for easy and performant multi-GPU/multi-node mixed-precision training. Supported models: Jasper, QuartzNet, CitriNet, Conformer-CTC, Conformer-Transducer, Squeezeformer-CTC, Squeezeformer-Transducer, ContextNet, LSTM-Transducer (RNNT), LSTM-CTC. ... -
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SimpleEnglish
Agent skill: make LLMs write docs in ASD-STE100
...The repository includes a complete skill, reusable system prompts, examples, evaluations, and a compact version for limited context budgets. It works with Agent Skills-compatible tools such as Claude Code, Cursor, Codex, Copilot, Gemini CLI, Goose, and OpenCode. Users without native skill support can paste the provided prompt into chatbot instructions or project configuration files. -
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AI Agent Book
Deep Understanding AI Agents
...Later material covers evaluation, supervised fine-tuning, reinforcement learning, self-improvement, multimodal interaction, robotics, and multi-agent cooperation. The repository includes 88 companion experiments, with more than 70 designed to run independently. Readers can access the source chapters, generated figures, code, and downloadable PDF or EPUB editions. Community translations provide versions in several languages alongside the original Chinese text. -
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SIA
AI framework to autonomously improve the performance of any AI system
...It uses an iterative loop where a meta-agent creates or updates a task-specific target agent, while a feedback agent studies results and proposes improvements. The framework can refine both the harness around the task and the agent implementation itself. It is aimed at research and experimentation across tasks such as machine learning benchmarks, legal classification, code optimization, and scientific workflows. It includes built-in tasks, a command-line runner, and a visual dashboard for following generations as they evolve. ... -
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Ideogram 4
Open image model at the forefront of design
...It is built for users who need more than generic image generation, especially when layout, typography, composition, color, and language understanding matter. The project introduces a structured JSON prompting workflow that gives creators more explicit control over scene details and visual constraints. It can also accept plain-text prompts, making it accessible to users who prefer a simpler generation style. Ideogram 4 is especially useful for design-heavy outputs such as posters, ads, mockups, branded graphics, and images that include readable text. Its main value is combining open model access with professional-level control over image structure and visual direction. -
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My Python Eggs
Python Examples
My Python Eggs, commonly associated with the geekcomputers Python repository, is a large collection of practical Python scripts and small programs created primarily for experimentation, automation, and educational purposes. Rather than being a single cohesive application, it functions as a repository of utilities that demonstrate how Python can be used to solve everyday problems and automate repetitive tasks. The scripts cover a wide range of topics, including file management, networking, system monitoring, web scraping, and even simple games, making it a versatile learning resource. Many of the programs are designed to reduce manual workload by automating tasks such as renaming files, scanning directories, or checking system information. ... -
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OpenHome Abilities
Open-source abilities for OpenHome agents
OpenHome Abilities is an open-source repository of modular voice AI plugins created for OpenHome agents, giving developers a lightweight way to extend what an agent can do through spoken triggers. Each ability is intentionally simple in structure, centering on a single main.py file that contains the core Python logic, which lowers the barrier to building and sharing custom behaviors. The system is meant to support a wide range of voice-driven actions, from API calls and media playback to quiz flows, device control, and multi-turn conversations, so it functions as a practical extension framework rather than a narrow template library. ... -
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Hephaestus
Semi-Structured Agentic Framework. Workflows build themselves
...The system continuously monitors agent behavior and task progression, allowing workflows to evolve as new discoveries are made. For example, if an agent detects a bug or optimization opportunity, it can automatically create a new task and integrate it into the workflow. The framework also includes monitoring mechanisms that track agent trajectories and ensure that tasks remain aligned with overall objectives. -
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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CodeGen
Open-source model for program synthesis
...This allows them to translate natural language descriptions into functional code across a variety of programming languages. CodeGen supports multi-turn program synthesis, meaning it can generate complex programs through a sequence of prompts that progressively refine the solution. The project also includes training infrastructure and model checkpoints that allow researchers to experiment with different model sizes and training configurations. Its architecture and training approach enable the models to perform competitively with proprietary coding models on benchmark tasks. -
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Happy-LLM
Large Language Model Principles and Practice Tutorial from Scratch
...The project guides learners through the entire conceptual and practical pipeline of modern LLM development, starting with foundational natural language processing concepts and gradually progressing to advanced architectures and training techniques. It explains the Transformer architecture, pre-training paradigms, and model scaling strategies while also providing hands-on coding examples so readers can implement and experiment with their own models. The tutorial emphasizes practical understanding by walking users through building and training small language models, including tokenizer construction, pre-training workflows, and fine-tuning methods. -
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MemOS
AI memory OS for LLM and Agent systems
MemOS is an experimental operating system and runtime built around the concept of memory-centric computing, where memory objects are first-class citizens and program execution is organized around efficient, persistent memory access rather than traditional process and file system boundaries. The project explores rethinking system abstractions by tightly coupling computation with memory objects so that programs can operate on large datasets without expensive serialization or context switching. It aims to support advanced workflows like persistent in-memory data structures, crash-resilient state handling, and seamless sharing of data across tasks without copying. By abandoning some of the historical assumptions of Unix-style operating systems, MemOS attempts to unlock new performance and scalability tradeoffs for applications that need high throughput and low latency on memory-intensive workloads. -
13
StoryMem
Official code for StoryMem: Multi-shot Long Video Storytelling
StoryMem is a narrative-focused memory accumulation system that lets users build, store, and reference past conversational context or story elements with an AI, effectively enabling the AI to maintain and recall personalized story memories or character arcs over time. Instead of treating each interaction as stateless, it tracks user-defined memory nodes, tags, and story threads so that future interactions can draw on established narrative context like character traits, past events, or ongoing plotlines. This makes it especially valuable for applications like AI-enriched storytelling, long-term role-playing, personal journaling assistants, or persistent game worlds where continuity and coherence matter. StoryMem includes tools to define, edit, and review saved memories, letting users manage what should be retained, forgotten, or emphasized in later conversations. -
14
fast-stable-diffusion
Fast-stable-diffusion + DreamBooth
...Rather than being a standalone packaged application, this project offers ready-to-use interactive notebooks that install and launch full-feature Stable Diffusion web UIs inside Colab without requiring complex local setups or GPU installations. Users can run both AUTOMATIC1111’s interface and ComfyUI workflows with minimal configuration, experiment with DreamBooth fine-tuning, and explore features like text-to-image generation, inpainting, and image-to-image transformations all within a browser session. Because it is configured for Colab, the project leverages Colab’s hosted GPUs, making it possible to use Stable Diffusion even without a powerful local GPU. -
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Habit Tracker
Habit Tracker for the AI Coding Workshop
...A calendar view lets users see a monthly grid of their habit history with color-coded days to highlight patterns and encourage daily engagement. Habit-Tracker also supports planned absences so users can skip days without breaking their streaks, reducing frustration and keeping long-term habits on track. -
16
Cua
Open-source infrastructure for Computer-Use Agents. Sandboxes
...It introduces a declarative syntax for specifying build scripts, automation pipelines, environment setups, and project-specific commands so contributors don’t need to memorize disparate scripts or tooling across languages and ecosystems. Cua can also manage task dependencies, handle cross-platform invocations, and simplify complex workflows into simple aliases or compound commands that are easy to share in teams. By centralizing shared commands in a structured, documented config, it helps reduce errors, accelerates onboarding of new contributors, and keeps task definitions versioned with the codebase. ... -
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Anomalib
An anomaly detection library comprising state-of-the-art algorithms
...It provides implementations of leading anomaly detection methods drawn from current research, as well as a full set of utilities for training, evaluating, benchmarking, and deploying these models on both public and private datasets. Anomalib emphasizes flexibility and reproducibility: you can use its simple APIs to plug in custom models, track experiments, tune hyperparameters, and generate visualizations that highlight anomalous regions. Its design supports unsupervised or semi-supervised paradigms, making it especially powerful for scenarios where only “normal” data is readily available and defects must be detected without exhaustive labeling. ... -
18
SleepFM-Clinical
Improve human sleep through scientifically
...Rather than simply playing static white noise or ambient tracks, it uses a closed-loop, frequency-modulated framework that responds to user-specific sleep patterns and physiological signals to tailor sound in ways that can enhance sleep onset and depth. The clinical release includes additional features for controlled experimentation, such as logging capabilities, adjustable parameter sets, and protocols suitable for sleep studies and therapeutic settings. It also integrates tools for clinicians to configure sessions, annotate events, and potentially link with biofeedback data, enabling a more nuanced understanding of sound’s effect on sleep architecture over time. -
19
pangu.py
Paranoid text spacing in Python
...Mixed-script text often becomes cramped or ambiguous, and this library applies simple but effective typography rules to make it instantly more readable. It works both as a Python library and a command-line utility, so you can process strings in code, tidy files in bulk, or wire it into documentation and build pipelines. The transformation is idempotent: running it multiple times won’t keep adding spaces, which makes it safe in automated workflows. It’s designed to be pragmatic and lightweight, with sensible defaults that handle common edge cases found in websites, blogs, and multilingual technical docs. ... -
20
Swift Numerics
Advanced mathematical types and functions for Swift
Swift Numerics is a foundational library that extends the Swift standard library with essential numerical protocols, types, and functions needed for scientific and systems programming. It defines generic abstractions over real and complex numbers so algorithms can be written once and work across concrete floating-point types. The package includes RealModule utilities and a full Complex type with the expected arithmetic and transcendental functions, bridging a long-standing gap for numerics in Swift. API design follows Swift’s emphasis on value semantics and protocol-oriented programming, enabling compiler optimizations and predictable performance. ... -
21
Lambda Builders
Python library to compile, build & package AWS Lambda functions
...We provide a generic Python runner to implement such build actions. A build action is a module that knows how to build for a particular programming language & framework (ex: Python+PIP). Build actions can be implemented in Python or in the native programming language. Each build action has its own design document. -
22
HelloGitHub
Share interesting, entry-level open source projects on GitHub
...It is updated and released in the form of a monthly magazine on the 28th of every month. The content includes interesting, entry-level open-source projects, open-source books, practical projects, enterprise-level projects, etc., so that you can feel the charm of open source in a short time and fall in love with open source! At first, I just wanted to collect interesting, high-quality, and easy-to-use projects that I found in the process of browsing GitHub, so that it would be easier to find and learn later. Later, I plan to share these interesting and valuable open source projects with you. ... -
23
Sa2VA
Official Repo For "Sa2VA: Marrying SAM2 with LLaVA
...It merges the segmentation power of a state-of-the-art video segmentation model (based on SAM‑2) with the vision-language reasoning capabilities of a strong LLM backbone (derived from models like InternVL2.5 / Qwen-VL series), yielding a system that can answer questions about visual content, perform referring segmentation, and maintain temporal consistency across frames in video. With minimal instruction tuning (often one-shot), Sa2VA can handle tasks such as “segment the main subject,” “what are the objects in this scene?”, or “track this object through the video,” outputting pixel-perfect masks or spoken/textual answers as appropriate. -
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Step1X-3D
High-Fidelity and Controllable Generation of Textured 3D Assets
...TSDF surface), and a texture synthesis stage that conditions on geometry and optionally reference input (or prompts) to produce view-consistent textures using a diffusion-based texture module. The result is fully 3D assets — meshes + textures — which can be rendered from any viewpoint, textured consistently, and used in 3D applications. To achieve this, the project includes a massive curated dataset: among more than 5 million candidate 3D assets, it filters and standardizes to produce a high-quality 2 million–asset subset suitable for training. -
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Step-Audio
Open-source framework for intelligent speech interaction
...Through its architecture, Step-Audio supports multilingual interaction, dialects, emotional tones (joy, sadness, etc.), and even more creative speech styles (like rap or singing), while allowing dynamic control over speech characteristics. It also provides a “generative data engine,” which can produce synthetic speech data (cloning voices, varying style) to support TTS training.
