Search Results for "aim"
Sort By:
Showing 87 open source projects for "aim"
View related business solutions-
$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.
-
Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
-
1
Aim
An easy-to-use & supercharged open-source experiment tracker
Aim logs all your AI metadata (experiments, prompts, etc) enabling a UI to compare & observe them and SDK to query them programmatically. The Aim standard package comes with all integrations. If you'd like to modify the integration and make it custom, create a new integration package and share with others. Aim is an open-source, self-hosted AI Metadata tracking tool designed to handle 100,000s of tracked metadata sequences. -
2
Lightweight' GAN
Implementation of 'lightweight' GAN, proposed in ICLR 2021
...The general recommendation is to use suitable augs for your data and as many as possible, then after some time of training disable the most destructive (for image) augs. You can turn on automatic mixed precision with one flag --amp. You should expect it to be 33% faster and save up to 40% memory. Aim is an open-source experiment tracker that logs your training runs, and enables a beautiful UI to compare them. -
3
Andrew NG Notes Collection
This is Andrew NG Coursera Handwritten Notes
...The project summarizes the key topics covered in the course, including supervised learning, neural networks, optimization algorithms, and model evaluation techniques. The notes aim to simplify complex mathematical explanations by organizing concepts into clear sections with diagrams, formulas, and concise descriptions. Each chapter mirrors the structure of the course curriculum, allowing students to review the material in a systematic way while following along with the lectures. The repository emphasizes conceptual clarity and practical understanding, helping learners connect mathematical foundations with real machine learning applications. -
4
TorchAudio
Data manipulation and transformation for audio signal processing
The aim of torchaudio is to apply PyTorch to the audio domain. By supporting PyTorch, torchaudio follows the same philosophy of providing strong GPU acceleration, having a focus on trainable features through the autograd system, and having consistent style (tensor names and dimension names). Therefore, it is primarily a machine learning library and not a general signal processing library. -
Save Up to 91% on Cloud Compute With Spot VMsRun batch jobs at 60-91% off with Spot VMs. Long-running workloads get automatic discounts with sustained use.
-
5
PearAI
The Open Source AI-Powered Code Editor. A fork of VSCode and Continue
...PearAI's goal is to reduce the time it takes for an individual to go from idea to creation. Coding itself is a crucial tool in product development, and we believe that with the advancement of AI, it may drastically change over the coming years. We aim to build the environment that will encompass these changes, both in the short-term and long-term. -
6
OpenMLSys-ZH
Machine Learning Systems: Design and Implementation
This repository is the Chinese translation (or localization) of the OpenMLSys project documentation. Its aim is to make the technical content, tutorials, architecture descriptions, and user guides of the OpenMLSys system more accessible to Chinese-speaking users. The repo mirrors the structure of the original OpenMLSys docs: sections on system design, API references, deployment instructions, module overviews, and example workflows. It helps bridge language barriers in open machine learning systems by providing side-by-side translation or localized explanations. ... -
7
Tongyi DeepResearch
Tongyi Deep Research, the Leading Open-source Deep Research Agent
...It uses a mix of synthetic data generation, fine-tuning and reinforcement learning; supports benchmarks like web search, document understanding, question answering, “agentic” tasks; provides inference tools, evaluation scripts, and “web agent” style interfaces. The aim is to enable more autonomous, agentic models that can perform sustained knowledge gathering, reasoning, and synthesis across multiple modalities (web, files, etc.). -
8
History LLMs
Information hub for our project training the largest possible LLMs
History LLMs serves as the central information hub for a research project focused on training large language models exclusively on historical texts up to specified cutoff dates, essentially creating time-locked AI that speaks from within a particular era’s worldview. The History LLMs aim to be trained on massive curated datasets of time-stamped documents so that the resulting models can offer responses grounded only in the knowledge available before their cutoff, such as 1913, thereby avoiding hindsight contamination common in modern LLMs. This approach enables researchers in the humanities and social sciences to explore how people at different historical moments would have discussed world events, norms, and ideas without later developments influencing the model. ... -
9
ByteHook
ByteHook is an Android PLT hook library
ByteHook is a ByteDance-hosted project whose name suggests a hooking or instrumentation library, likely used for hooking system calls or API calls for monitoring, sandboxing or instrumentation. The repository appears to aim at low-level hooking/injection capabilities, perhaps to support runtime introspection, behavioral monitoring, or hooking-based instrumentation (e.g. for security, tracing, sandboxing, or debugging). Because hooking is a common technique for intercepting library or system calls, Bhook likely provides abstractions to inject hooks into processes or libraries, enabling custom behavior monitoring or modification — which can be useful for building security tools, monitoring frameworks, or dynamic instrumentation. ... -
Fully Managed MySQL, PostgreSQL, and SQL ServerCloud SQL handles your database ops end to end, so you can focus on your app.
-
10
LMCache
Supercharge Your LLM with the Fastest KV Cache Layer
...Its design supports reuse beyond strict prefix matching and enables sharing across serving instances, improving efficiency under real multi-tenant traffic. The broader project includes examples, tests, a server component, and public posts describing cross-engine sharing and inter-GPU KV transfers. These capabilities aim to lower latency, cut GPU cycles, and stabilize performance for production workloads with overlapping prompts or retrieval-augmented contexts. The end result is a cache fabric for LLMs that complements engines rather than replacing them. -
11
Purple Llama
Set of tools to assess and improve LLM security
...CyberSecEval, one of its flagship components, provides repeatable evaluations for security risk, including agent-oriented tasks such as automated patching benchmarks. The aim is to make safety practical: ship testable baselines, publish metrics, and provide drop-in implementations that reduce friction for teams adopting Llama. Documentation and sites attached to the repo walk through setup, usage, and the rationale behind each safeguard, encouraging community contributions. -
12
3FS
A high-performance distributed file system
The 3FS repository (standing likely for “Feature 3F System” or similar) is focused on providing a feature extraction and transformation framework tailored to deep and large models, especially in token-based systems. Its primary aim is to support efficient and scalable feature transformation pipelines—especially for inference environments—by batching, caching, and integrating feature-based modules like segmenters, sparse retrievers, and scorers seamlessly. The repo includes APIs to define components (e.g. seg, ret, scor) that wrap or interface with external or internal modules, as well as logic to schedule and compose these feature transforms. ... -
13
Colossal-AI
Making large AI models cheaper, faster and more accessible
...It remains a challenge for AI researchers to implement complex distributed training solutions for their models. Colossal-AI provides a collection of parallel components for you. We aim to support you to write your distributed deep learning models just like how you write your model on your laptop. -
14
TensorFlow Model Garden
Models and examples built with TensorFlow
The TensorFlow Model Garden is a repository with a number of different implementations of state-of-the-art (SOTA) models and modeling solutions for TensorFlow users. We aim to demonstrate the best practices for modeling so that TensorFlow users can take full advantage of TensorFlow for their research and product development. To improve the transparency and reproducibility of our models, training logs on TensorBoard.dev are also provided for models to the extent possible though not all models are suitable. ... -
15
Scene Framework
Android Single Activity Framework compatible with Fragment
...Given ByteDance’s broad portfolio, Scene could be an internal or external library for structuring application “scenes” (UI, media, game, or module-level) or orchestrating workflows in a modular fashion. The repository may aim to help developers manage complex state, transitions, or UI/navigation flows in applications, or provide a structured framework for rendering or content pipelines. As such, Scene could serve as a backbone for media apps, games, or modular user interface projects, offering abstractions for scene management, resource loading, event dispatching, and lifecycle handling. ... -
16
windsurf.vim
Free, ultrafast Copilot alternative for Vim and Neovim
windsurf.vim is a plugin for Vim and Neovim by Exafunction (formerly part of the Codeium project) that brings in AI-driven code completion and assistance capabilities. The aim is to provide a “free, ultrafast” alternative to other AI code assistants (such as GitHub Copilot) directly within Vim/Neovim. Once installed and configured, windsurf.vim can suggest code completions, generate multi-line snippets based on comments or invitation in code, and make the editing experience more predictive and context-aware. ... -
17
satellite-image-deep-learning
Resources for deep learning with satellite & aerial imagery
...Note there is a huge volume of academic literature published on these topics, and this repository does not seek to index them all but rather list approachable resources with published code that will benefit both the research and developer communities. If you find this work useful please give it a star and consider sponsoring it. You can also follow me on Twitter and LinkedIn where I aim to post frequent updates on my new discoveries, and I have created a dedicated group on LinkedIn. I have also started a blog here and have published a post on the history of this repository called Dissecting the satellite-image-deep-learning repo. -
18
Errbot
Chatbot daemon that connects to your favorite chat services
...Extending Errbot and adding your own commands can be done by creating a plugin, which is simply a class derived from BotPlugin. The docstrings will be automatically reused by the !help command. We aim to give you all the tools you need to build a customized bot safely, without having to worry about basic functionality. As such, Errbot comes with a wealth of features out of the box. One of the main goals of Errbot is to make it easy to share your plugin with others as well. -
19
UNO
A Universal Customization Method for Single and Multi Conditioning
...It suggests a framework for image (or more general generative) modeling where the model can be conditioned either on a single subject or multiple subjects — which may correspond to generating or customizing images featuring specific people, styles, or objects, possibly with fine-grained control over subject identity or composition. Because the project is new (see activity logs for 2025), it seems to aim at bridging between single-subject customization and multi-subject generation in generative modeling — potentially useful for personalized content creation, flexible composition, or controlled generation tasks. UNO likely offers tools to fine-tune or condition generation models so that they can incorporate novel subjects, enabling users to produce custom outputs beyond standard training distribution. -
20
008
Open-source event-driven AI powered Softphone
...It is also accessible on the web (though official support for browser-related issues is not provided). The name '008' or 'agent 008' reflects our ambition: beyond crafting the premier Open Source Softphone, we aim to introduce a programmable, event-driven AI agent. This agent utilizes embedded artificial intelligence models operating directly on the softphone, ensuring efficiency and reduced operational costs. This project is a WebRTC softphone, and communication is achieved via SIP over a socket. Leading PBX systems like Asterisk or Freeswitch support socket connections. ... -
21
AI-Aimbot
CS2, Valorant, Fortnite, APEX, every game
...The system uses an object detection model based on the YOLOv5 architecture to detect human-shaped characters in gameplay screenshots or video frames. Once a target is identified, the program automatically adjusts the player’s aim toward the detected target, effectively automating the aiming process in first-person shooter games. The project emphasizes that it is intended for educational purposes to illustrate potential vulnerabilities in game design and anti-cheat systems. Because the system relies solely on visual detection rather than reading game memory, it attempts to bypass certain traditional anti-cheat detection methods. -
22
solo-learn
Library of self-supervised methods for visual representation
A library of self-supervised methods for visual representation learning powered by Pytorch Lightning. A library of self-supervised methods for unsupervised visual representation learning powered by PyTorch Lightning. We aim at providing SOTA self-supervised methods in a comparable environment while, at the same time, implementing training tricks. The library is self-contained, but it is possible to use the models outside of solo-learn. -
23
State of Open Source AI
Clarity in the current fast-paced mess of Open Source innovation
...It acts as both a snapshot and a guide: readers can see what’s “hot now” in open AI infrastructure, what open licensing or governance issues are emerging, how deployment options compare, and what gaps remain. Because the AI domain moves quickly, part of the aim is to make the content maintainable and updateable by the community. The structure includes chapters or sections about model formats, evaluation benchmarks, hardware/backends, MLOps systems, alignment and safety issues, and open datasets. The repository contains the text (in Markdown or similar), configuration for build or publishing (static site or e-book), and contributor guidelines. -
24
Consistency Models
Official repo for consistency models
consistency_models is the repository for Consistency Models, a new family of generative models introduced by OpenAI that aim to generate high-quality samples by mapping noise directly into data — circumventing the need for lengthy diffusion chains. It builds on and extends diffusion model frameworks (e.g. based on the guided-diffusion codebase), adding techniques like consistency distillation and consistency training to enable fast, often one-step, sample generation. -
25
MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack