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Showing 3021 open source projects for "python windows"
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AI-Aimbot
CS2, Valorant, Fortnite, APEX, every game
AI-Aimbot is a computer vision project that demonstrates how artificial intelligence can be used to automatically identify and target opponents in video games. 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... -
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YAYI
Repo for YaYi Chinese LLMs based on LlaMA2 & BLOOM
YAYI is an open-source large language model project developed to provide a multilingual conversational AI system capable of performing a wide variety of natural language processing tasks. The model is trained on diverse datasets covering multiple languages and domains so that it can support applications ranging from dialogue systems to text analysis and knowledge retrieval. The architecture is based on transformer-style language models optimized for conversational understanding and... -
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BIG-bench
Beyond the Imitation Game collaborative benchmark for measuring
BIG-bench (Beyond the Imitation Game Benchmark) is a large, collaborative benchmark suite designed to probe the capabilities and limitations of large language models across hundreds of diverse tasks. Rather than focusing on a single metric or domain, it aggregates many hand-authored tasks that test reasoning, commonsense, math, linguistics, ethics, and creativity. Tasks are intentionally heterogeneous: some are multiple-choice with exact scoring, others are free-form generation judged by... -
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Sonnet
TensorFlow-based neural network library
Sonnet is a neural network library built on top of TensorFlow designed to provide simple, composable abstractions for machine learning research. Sonnet can be used to build neural networks for various purposes, including different types of learning. Sonnet’s programming model revolves around a single concept: modules. These modules can hold references to parameters, other modules and methods that apply some function on the user input. There are a number of predefined modules that already... -
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Punica
Serving multiple LoRA finetuned LLM as one
Punica is a system designed to efficiently serve multiple LoRA-fine-tuned large language models within a shared GPU environment. LoRA is a parameter-efficient fine-tuning method that allows developers to adapt large pretrained models to specific tasks by adding lightweight adapter layers rather than retraining the entire model. Punica introduces a serving architecture that allows multiple LoRA adapters to share the same base model during inference, significantly reducing memory consumption... -
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Firefly LLM
A large model training tool that supports training large models
Firefly is an open-source framework designed to simplify the training and fine-tuning of large language models through a unified and configurable workflow. The project provides a comprehensive environment where developers can perform tasks such as model pre-training, instruction tuning, and preference optimization using widely adopted machine learning techniques. Its architecture supports both full-parameter training and parameter-efficient strategies like LoRA and QLoRA, making it suitable... -
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SSD in PyTorch 1.0
High quality, fast, modular reference implementation of SSD in PyTorch
This repository implements SSD (Single Shot MultiBox Detector). The implementation is heavily influenced by the projects ssd.pytorch, pytorch-ssd and maskrcnn-benchmark. This repository aims to be the code base for research based on SSD. Multi-GPU training and inference: We use DistributedDataParallel, you can train or test with arbitrary GPU(s), the training schema will change accordingly. Add your own modules without pain. We abstract backbone, Detector, BoxHead, BoxPredictor, etc. You can... -
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PromptTools
Open-source tools for prompt testing and experimentation
Welcome to prompttools created by Hegel AI! This repo offers a set of open-source, self-hostable tools for experimenting with, testing, and evaluating LLMs, vector databases, and prompts. The core idea is to enable developers to evaluate using familiar interfaces like code, notebooks, and a local playground. -
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Extended Dreambooth How-To Guides
Implementation of Dreambooth
Extended Dreambooth How-To Guides is an implementation and extended toolkit for fine-tuning Stable Diffusion models using the DreamBooth technique, enabling users to train AI image generators to reproduce specific subjects, styles, or identities from a small set of reference images. The project adapts and expands upon earlier DreamBooth research by providing practical scripts, notebooks, and workflows that allow users to train personalized models on local machines, cloud environments, or... -
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YYeTsBot
Renren Film and Television bot, fully connected to Renren resources
Renren Film and Television bot, fully connected to all Renren Film and television resources without deletion of resources. The database of this site is permanently open source and free. You can directly send the name of the episode you want to watch, and you can choose to share the webpage or link (ed2k and magnet links). When searching for resources, it will be searched according to my predetermined priority (everyone video offline, subtitle man), of course, you can also use commands to... -
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ChatArena
ChatArena (or Chat Arena) is a Multi-Agent Language Game Environments
ChatArena is a library that provides multi-agent language game environments and facilitates research about autonomous LLM agents and their social interactions. -
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Mixtral offloading
Run Mixtral-8x7B models in Colab or consumer desktops
Mixtral-Offloading is an open-source project designed to enable efficient inference of large Mixture-of-Experts language models such as Mixtral-8x7B on hardware with limited GPU memory. The project implements techniques that allow model components to be dynamically moved between CPU memory and GPU memory during inference, significantly reducing the amount of GPU VRAM required to run the model. This approach takes advantage of the sparse activation properties of mixture-of-experts... -
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Functionary
Chat language model that can use tools and interpret the results
Functionary is an open-source large language model specifically designed for interpreting and executing structured functions or external tools within conversational AI systems. The model extends traditional chat-based language models by enabling them to determine when external functions should be called and how to extract the necessary parameters from natural language input. Function definitions are typically provided in JSON schema format, allowing the model to generate structured function... -
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RWKV
RNN with great LLM performance
RWKV-LM is the main research and training repository for the RWKV language model architecture. It presents RWKV as an attention-free RNN-style model that aims to reach transformer-level language model performance. The project is built around the idea that a model can be trained in a parallelizable way like a GPT-style transformer while running inference with recurrent efficiency. This gives RWKV important advantages for long-context use, including lower memory pressure and no traditional... -
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LLaMA-MoE
Building Mixture-of-Experts from LLaMA with Continual Pre-training
LLaMA-MoE is an open-source project that builds mixture-of-experts language models from LLaMA through expert partitioning and continual pre-training. The repository is centered on making MoE research more accessible by offering smaller and more affordable models with only about 3.0 to 3.5 billion activated parameters, which helps reduce deployment and experimentation costs. Its architecture works by splitting LLaMA feed-forward networks into sparse experts and adding gating mechanisms so... -
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EmotiVoice
Multi-Voice and Prompt-Controlled TTS Engine
EmotiVoice is a multi-voice, prompt-controlled text-to-speech engine designed to generate highly expressive speech across thousands of voices. It supports both English and Chinese and ships with over 2,000 preset voices, making it suitable for everything from characters and virtual anchors to narration and dialogue. The core idea is prompt-based emotional and style control: you can ask the engine to speak “happy,” “sad,” “excited,” or with other high-level style prompts that shape prosody,... -
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BackgroundMattingV2
Real-Time High-Resolution Background Matting
Official repository for the paper Real-Time High-Resolution Background Matting. Our model requires capturing an additional background image and produces state-of-the-art matting results at 4K 30fps and HD 60fps on an Nvidia RTX 2080 TI GPU. -
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ChatGPT-Reviewer
Automated pull requests reviewing and issues triaging with ChatGPT
Automated pull requests reviewing and issues triaging with ChatGPT. Create an OpenAI API key here, and then set the key as an action secret in your repository named OPENAI_API_KEY. The ChatGPT reviewer PRs are also getting reviewed by ChatGPT, refer the pull requests for the sample review comments. In order to protect public repositories for malicious users, Github runs all pull request workflows raised from repository forks with a read-only token and no access to secrets. -
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InternLM
Official release of InternLM series
InternLM is an open-source family of multilingual foundation and chat models, accompanied by an ecosystem that supports training, inference, and application development. The repository highlights multiple model sizes intended to serve different needs, from efficient research and prototyping to more capable deployments for complex scenarios. Beyond model weights, the project emphasizes an ecosystem view, pointing developers to compatible tools and projects across training and inference so... -
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Coqui TTS
A deep learning toolkit for Text-to-Speech, battle-tested in research
TTS is a library for advanced Text-to-Speech generation. It's built on the latest research, was designed to achieve the best trade-off among ease-of-training, speed and quality. TTS comes with pre-trained models, tools for measuring dataset quality and is already used in 20+ languages for products and research projects. High-performance Deep Learning models for Text2Speech tasks. Text2Spec models (Tacotron, Tacotron2, Glow-TTS, SpeedySpeech). Speaker Encoder to compute speaker embeddings... -
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MMDeploy
OpenMMLab Model Deployment Framework
MMDeploy is an open-source deep learning model deployment toolset. It is a part of the OpenMMLab project. Models can be exported and run in several backends, and more will be compatible. All kinds of modules in the SDK can be extended, such as Transform for image processing, Net for Neural Network inference, Module for postprocessing and so on. Install and build your target backend. ONNX Runtime is a cross-platform inference and training accelerator compatible with many popular ML/DNN... -
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Resemble Enhance
AI powered speech denoising and enhancement
Resemble Enhance is an AI-powered speech enhancement tool focused on improving the quality of recorded or generated voice audio. It combines denoising and enhancement so speech can sound cleaner, clearer, and more polished. The denoising module separates speech from unwanted background noise, while the enhancement module improves perceptual quality by restoring distortions and extending audio bandwidth. It is useful for voice datasets, podcasts, narration, generated speech, and other... -
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CLIP-as-service
Embed images and sentences into fixed-length vectors
CLIP-as-service is a low-latency high-scalability service for embedding images and text. It can be easily integrated as a microservice into neural search solutions. Serve CLIP models with TensorRT, ONNX runtime and PyTorch w/o JIT with 800QPS[*]. Non-blocking duplex streaming on requests and responses, designed for large data and long-running tasks. Horizontally scale up and down multiple CLIP models on single GPU, with automatic load balancing. Easy-to-use. No learning curve, minimalist... -
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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. -
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GPT-2 Output Dataset
Dataset of GPT-2 outputs for research in detection, biases, and more
The GPT-2 Output Dataset is a large collection of model-generated text, released by OpenAI alongside the GPT-2 research paper to study the behaviors and limitations of large language models. It contains 250,000 samples of GPT-2 outputs, generated with different sampling strategies such as top-k truncation, to highlight the diversity and quality of model completions. The dataset also includes corresponding human-written text for comparison, enabling researchers to explore methods for...
