Search Results for "pixelos_beryllium-14"
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Showing 12 open source projects for "pixelos_beryllium-14"
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FreeLLMAPI
OpenAI-compatible proxy that aggregates free-tier keys from ~14 AI
FreeLLMAPI is an OpenAI-compatible proxy that aggregates free-tier API keys from multiple AI providers into one unified endpoint. It is designed for personal experimentation, testing, and lightweight development workflows where users want to route requests through several providers without rewriting client code for each one. The project can automatically fail over between configured providers when one is unavailable or exhausted. Its OpenAI-compatible design makes it easier to use with... -
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BaseRT
Fastest LLM inference runtime for Apple Silicon
BaseRT is a local large language model inference runtime optimized for Apple Silicon computers. It accelerates model execution through hand-written Metal kernels and requires an M1 or newer Mac running macOS 14 or later. A unified command-line interface can download models from Hugging Face, convert checkpoints, launch chats, benchmark performance, and inspect model packages. Its server implements OpenAI-compatible chat, completion, embedding, transcription, tool-calling, and multimodal endpoints. The custom .base format supports affine quantization from Q2 through Q8, optional AWQ calibration, and signed model bundles. ... -
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n8n-skills
n8n skillset for Claude Code to build flawless n8n workflows
n8n-skills is a Claude Code skill pack for building production-ready n8n workflows with the n8n-mcp MCP server. It gives AI assistants specialized guidance for n8n expression syntax, node configuration, workflow patterns, validation, error handling, binary data, sub-workflows, AI agents, Code nodes, and self-hosting. The project includes fourteen complementary skills plus a router and hook-based enforcement layer that surfaces the right guidance during workflow creation. It is designed to... -
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Claw Compactor
14-stage Fusion Pipeline for LLM token compression
Claw Compactor is a utility designed to optimize and manage the context limitations inherent in AI agent systems, particularly those built on OpenClaw-like architectures. It addresses the challenge of finite context windows in language models by compressing or summarizing historical interactions while preserving essential information. The system works by transforming older conversation data into condensed representations that maintain continuity without exceeding token limits. This approach... -
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eos
A lightweight 3D Morphable Face Model library in modern C++
eos is a lightweight 3D Morphable Face Model fitting library that provides basic functionality to use face models, as well as camera and shape fitting functionality. It's written in modern C++11/14. MorphableModel and PcaModel classes to represent 3DMMs, with basic operations like draw_sample(). Supports the Surrey Face Model (SFM), 4D Face Model (4DFM), Basel Face Model (BFM) 2009 and 2017, and the Liverpool-York Head Model (LYHM) out-of-the-box. -
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DeepDetect
Deep Learning API and Server in C++14 support for Caffe, PyTorch
The core idea is to remove the error sources and difficulties of Deep Learning applications by providing a safe haven of commoditized practices, all available as a single core. While the Open Source Deep Learning Server is the core element, with REST API, and multi-platform support that allows training & inference everywhere, the Deep Learning Platform allows higher level management for training neural network models and using them as if they were simple code snippets. Ready for applications... -
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Karlo
Text-conditional image generation model based on OpenAI's unCLIP
Karlo is a text-conditional image generation model based on OpenAI's unCLIP architecture with the improvement over the standard super-resolution model from 64px to 256px, recovering high-frequency details only in the small number of denoising steps. We train all components from scratch on 115M image-text pairs including COYO-100M, CC3M, and CC12M. In the case of Prior and Decoder, we use ViT-L/14 provided by OpenAI’s CLIP repository. Unlike the original implementation of unCLIP, we replace the trainable transformer in the decoder into the text encoder in ViT-L/14 for efficiency. In the case of the SR module, we first train the model using the DDPM objective in 1M steps, followed by additional 234K steps to fine-tune the additional component. -
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Discord Music Bot
An advanced discord music bot, supports Spotify, Soundcloud, YouTube
An advanced discord music bot, that supports Spotify, Soundcloud, and YouTube with Shuffling, Volume Control, and Web Dashboard with Slash Commands support! Discord.js v13 will break this bot so do not use this with it. We have been started working on v5 which will be out in some days/months with new features and much more are on the way. -
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Arabic Corpus
Text categorization, arabic language processing, language modeling
...Berkani, (2011) Evaluation of Topic Identification Methods on Arabic Corpora,JOURNAL OF DIGITAL INFORMATION MANAGEMENT,vol. 9, N. 5, pp.185-192. 2) For Khaleej-2004 corpus --------------------------------- M. Abbas, K. Smaili (2005) Comparison of Topic Identification Methods for Arabic Language, RANLP05 : Recent Advances in Natural Language Processing ,pp. 14-17, 21-23 september 2005, Borovets, Bulgary. More useful references to check: ------------------------------------------- https://sites.google.com/site/mouradabbas9/corpora -
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RealSpeech is a simple and basic Text-to-Speech Software. RealSpeech will take in text written in English and will make your computer speak it out. Programed in C#. Real Speech is my second major C# project as a 14-year old kid. RealSpeech will run on Windows 8/8.1 and 10. For Windows 7 or earlier you will have to install the latest version of .NET Framework to run RealSpeech. Check out my previous C# project "Bruv" at: sourceforge.net/projects/bruv Thank You!
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tiny-dnn
header only, dependency-free deep learning framework in C++14
tiny-dnn is a C++14 implementation of deep learning. It is suitable for deep learning on limited computational resources, embedded systems, and IoT devices. -
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CLIP-ViT-bigG-14-laion2B-39B-b160k
CLIP ViT-bigG/14: Zero-shot image-text model trained on LAION-2B
CLIP-ViT-bigG-14-laion2B-39B-b160k is a powerful vision-language model trained on the English subset of the LAION-5B dataset using the OpenCLIP framework. Developed by LAION and trained by Mitchell Wortsman on Stability AI’s compute infrastructure, it pairs a ViT-bigG/14 vision transformer with a text encoder to perform contrastive learning on image-text pairs.
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