Search Results for "s-parameters"
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Showing 398 open source projects for "s-parameters"
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DeepSeek R1
Open-source, high-performance AI model with advanced reasoning
...DeepSeek R1 offers unrestricted access for both commercial and academic use. The model employs a Mixture of Experts (MoE) architecture, comprising 671 billion total parameters with 37 billion active parameters per token, and supports a context length of up to 128,000 tokens. DeepSeek-R1's training regimen uniquely integrates large-scale reinforcement learning (RL) without relying on supervised fine-tuning, enabling the model to develop advanced reasoning capabilities. This approach has resulted in performance comparable to leading models like OpenAI's o1, while maintaining cost-efficiency. ... -
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GLM-4.5
GLM-4.5: Open-source LLM for intelligent agents by Z.ai
GLM-4.5 is a cutting-edge open-source large language model designed by Z.ai for intelligent agent applications. The flagship GLM-4.5 model has 355 billion total parameters with 32 billion active parameters, while the compact GLM-4.5-Air version offers 106 billion total parameters and 12 billion active parameters. Both models unify reasoning, coding, and intelligent agent capabilities, providing two modes: a thinking mode for complex reasoning and tool usage, and a non-thinking mode for immediate responses. ... -
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Maigret
Collect a dossier on a person by username from thousands of sites
Maigret is an open-source OSINT tool designed to collect a dossier on a person by username from thousands of sites. It automates the process of checking for a user's presence across various platforms, aiding in digital investigations. -
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Copulas
A library to model multivariate data using copulas
...Compare real and synthetic data visually after building your model. Visualizations are available as 1D histograms, 2D scatterplots and 3D scatterplots. Access & manipulate learned parameters. With complete access to the internals of the model, set or tune parameters to your choosing. -
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Microsoft Azure CLI
Azure command-line interface
A great cloud needs great tools; we're excited to introduce Azure CLI, our next-generation multi-platform command-line experience for Azure. Take a test run now from Azure Cloud Shell! We support tab completion for groups, commands, and some parameters. You can use the --query parameter and the JMESPath query syntax to customize your output. With the Azure CLI Tools Visual Studio Code extension, you can create .azcli files and use these features. IntelliSense for commands and their arguments. Snippets for commands, inserting required arguments automatically. Run the current command in the integrated terminal. ... -
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MegaTTS 3
Official PyTorch Implementation
MegaTTS3 is an open-source text-to-speech (TTS) and voice-cloning system from ByteDance that aims to deliver high-quality, expressive speech synthesis, including zero-shot voice cloning of previously unseen speakers. Its backbone is a lightweight diffusion-transformer (on the order of ~0.45 B parameters), which enables efficient inference while still producing high-fidelity audio. Given a reference audio sample (and corresponding latent representation), MegaTTS3 can generate speech in the style and voice timbre of that speaker — useful for personalized TTS, voice-overs, dubbing, or multi-speaker applications. The system supports both Chinese and English (with code-switching), making it versatile across languages, and offers controls for accent strength, voice similarity, intelligibility vs. similarity tradeoffs, and other speech parameters to fine-tune output. -
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Torch Pruning
DepGraph: Towards Any Structural Pruning
Torch-Pruning is an open-source toolkit designed to optimize deep neural networks by performing structural pruning directly within PyTorch models. The library focuses on reducing the size and computational cost of neural networks by removing redundant parameters and channels while maintaining model performance. It introduces a graph-based algorithm called DepGraph that automatically identifies dependencies between layers, allowing parameters to be pruned safely across complex architectures. This dependency analysis makes it possible to prune large networks such as transformers, convolutional networks, and diffusion models without breaking the computational graph. ... -
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Sacred
Sacred is a tool to help you configure, andorganize IDSIA experiments
...It is designed to do all the tedious overhead work that you need to do around your actual experiment. A very convenient way of the local variables in a function to define the parameters your experiment uses. You can access all parameters of your configuration from every function. They are automatically injected by name. You get a powerful command-line interface for each experiment that you can use to change parameters and run different variants. Observers that log all kinds of information about your experiment, its dependencies, the configuration you used, the machine it is run on, and of course the result. ... -
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FastAPI
FastAPI framework, high performance, easy to learn, fast to code
...If you are building a CLI app to be used in the terminal instead of a web API, check out Typer. Typer is FastAPI's little sibling. And it's intended to be the FastAPI of CLIs. In summary, you declare once the types of parameters, body, etc. as function parameters. You do that with standard modern Python types. You don't have to learn a new syntax, the methods or classes of a specific library, etc. -
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10
Codex++
An enhanced tool for CodexApp, striving to make Codex better to use
Codex++ is an external enhancement launcher for Codex App that improves usability without modifying the original installation files. It works by launching Codex with Chromium DevTools Protocol parameters, running a local helper service, and injecting enhancement scripts into the renderer. The tool adds a dedicated Codex++ menu, unlocks plugin entry points in API Key mode, enables forced installation for unavailable plugins, and improves local session management. It also adds true session deletion with confirmation and undo, Markdown export with timestamps, conversation timeline navigation, and the ability to move sessions between normal chats and local projects. ... -
11
PEFT
State-of-the-art Parameter-Efficient Fine-Tuning
Parameter-Efficient Fine-Tuning (PEFT) methods enable efficient adaptation of pre-trained language models (PLMs) to various downstream applications without fine-tuning all the model's parameters. Fine-tuning large-scale PLMs is often prohibitively costly. In this regard, PEFT methods only fine-tune a small number of (extra) model parameters, thereby greatly decreasing the computational and storage costs. Recent State-of-the-Art PEFT techniques achieve performance comparable to that of full fine-tuning. -
12
ComfyUI SUPIR
SUPIR upscaling wrapper for ComfyUI
...It enables users to enhance low-resolution or degraded images using advanced diffusion-based techniques. The integration provides nodes that allow users to control parameters such as noise levels, guidance strength, and output quality. It is particularly useful for workflows that require upscaling or restoring images before further processing. The project leverages modern generative models to produce sharp, detailed outputs while preserving the original structure of the image. It can be combined with other ComfyUI nodes for tasks such as stylization or animation. ... -
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DeepSeek-V3
Powerful AI language model (MoE) optimized for efficiency/performance
DeepSeek-V3 is a robust Mixture-of-Experts (MoE) language model developed by DeepSeek, featuring a total of 671 billion parameters, with 37 billion activated per token. It employs Multi-head Latent Attention (MLA) and the DeepSeekMoE architecture to enhance computational efficiency. The model introduces an auxiliary-loss-free load balancing strategy and a multi-token prediction training objective to boost performance. Trained on 14.8 trillion diverse, high-quality tokens, DeepSeek-V3 underwent supervised fine-tuning and reinforcement learning to fully realize its capabilities. ... -
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Qwen3-TTS
Qwen3-TTS is an open-source series of TTS models
...Because it’s part of the broader Qwen ecosystem, it benefits from the model’s understanding of linguistic nuances, enabling more accurate pronunciation, prosody, and contextual delivery than many traditional TTS systems. Developers can customize voice output parameters like speed, pitch, and volume, and combine the TTS stack with other AI components. -
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MCP ZoomEye
A Model Context Protocol server that provides network asset info
The ZoomEye MCP Server is a Model Context Protocol server that provides network asset information based on query conditions, allowing Large Language Models to obtain data by querying ZoomEye using dorks and other search parameters. -
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LLM Telegram Bot
A Telegram bot for Large Language Models
...The project is designed to provide a customizable AI assistant that can operate within Telegram conversations, supporting dynamic responses based on user input and configurable parameters. It includes features such as conversation memory, allowing the bot to maintain context across multiple messages and provide more coherent responses. The system supports multiple modes or personas, enabling users to switch between different conversational styles or use cases. It also allows fine-tuning of generation parameters such as temperature and token limits, giving users control over response behavior. ... -
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crawler
Collection of JS reverse engineering examples for web scraping study
crawler is a collection of web scraping and JavaScript reverse engineering examples designed for learning how modern websites protect their data and how those protections can be analyzed. It contains many case studies that demonstrate how to analyze and replicate request parameters, cookies, and encryption logic used by real websites. Each directory in the project focuses on a specific target service or scenario, showing how browser network requests and JavaScript code can be studied to reproduce API calls programmatically. Many examples illustrate techniques such as debugging scripts, intercepting requests, analyzing encrypted parameters, and understanding authentication flows. crawler also explores common anti-scraping defenses and demonstrates how developers can examine them through debugging tools and reverse engineering techniques. -
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Haiku
JAX-based neural network library
...Similar to Sonnet modules, Haiku modules are Python objects that hold references to their own parameters, other modules, and methods that apply functions on user inputs. -
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TikTok-ViewBot
ViewBot using requests updated 2025
TikTok-ViewBot explores automated interactions with TikTok’s viewing mechanisms for research and educational purposes. The code demonstrates how scripted traffic might be generated and measured, highlighting the kinds of heuristics a platform could use to validate or discount views. It is often used to study rate limits, signature schemes, request patterns, and the fragility of naïve automation. Because it touches on automation against a third-party service, responsible use and adherence to... -
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PowerTrader_AI
Fully automated crypto trading powered by a custom price prediction AI
...The bot integrates with popular exchange APIs so it can execute real buy and sell orders, manage risk, and maintain position sizing without manual intervention, making it suitable for algorithmic traders who want hands-off operations. It also includes configurable settings so users can adjust strategies, risk parameters, and the assets to trade, giving flexibility for different market conditions. -
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ChatTTS webUI & API
A simple native web interface that uses ChatTTS to synthesize text
ChatTTS-ui is a local web interface and API wrapper around the ChatTTS speech synthesis system, designed to make advanced TTS models easy to use from a browser. It runs a small backend server (Python + Torch + ffmpeg) and exposes a simple webpage where you can type text, adjust parameters, and generate audio. The project supports Chinese, English, and mixed text with digits and control symbols, making it suitable for bilingual content and numerically heavy text like announcements or prompts. From version 0.96 onward, ffmpeg installation is required for deployment, and previous CSV/PT voice tables are no longer valid, so users instead work with updated “voice value” parameters. -
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reg-factory
Google Mail registration
...It uses local scripts and external tool integrations to coordinate browser profiles, network settings, Android-based Gmail workflows, and runtime logs. The included panel helps users launch scripts, fill parameters, monitor tool status, and review process output from one place. Because the project touches sensitive account-creation workflows, it should only be used in authorized, compliant, and non-abusive testing environments. -
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Qwen3-Coder
Qwen3-Coder is the code version of Qwen3
Qwen3-Coder is the latest and most powerful agentic code model developed by the Qwen team at Alibaba Cloud. Its flagship version, Qwen3-Coder-480B-A35B-Instruct, features a massive 480 billion-parameter Mixture-of-Experts architecture with 35 billion active parameters, delivering top-tier performance on coding and agentic tasks. This model sets new state-of-the-art benchmarks among open models for agentic coding, browser-use, and tool-use, matching performance comparable to leading models like Claude Sonnet. Qwen3-Coder supports an exceptionally long context window of 256,000 tokens, extendable to 1 million tokens using Yarn, enabling repository-scale code understanding and generation. ... -
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MobileLLM
MobileLLM Optimizing Sub-billion Parameter Language Models
...Introduced in the ICML 2024 paper “MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases”, it focuses on delivering strong reasoning and generalization capabilities in models under one billion parameters. The framework integrates several architectural innovations—SwiGLU activation, deep and thin network design, embedding sharing, and grouped-query attention (GQA)—to achieve a superior trade-off between model size, inference speed, and accuracy. MobileLLM demonstrates remarkable performance, with the 125M and 350M variants outperforming previous state-of-the-art models of the same scale by up to 4.3% on zero-shot commonsense reasoning tasks. -
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DeepSeed
Deep learning optimization library making distributed training easy
...DeepSpeed delivers extreme-scale model training for everyone, from data scientists training on massive supercomputers to those training on low-end clusters or even on a single GPU. Using current generation of GPU clusters with hundreds of devices, 3D parallelism of DeepSpeed can efficiently train deep learning models with trillions of parameters. With just a single GPU, ZeRO-Offload of DeepSpeed can train models with over 10B parameters, 10x bigger than the state of arts, democratizing multi-billion-parameter model training such that many deep learning scientists can explore bigger and better models. Sparse attention of DeepSpeed powers an order-of-magnitude longer input sequence and obtains up to 6x faster execution comparing with dense transformers.
