Finetune Llama 4, TTS, DeepSeek-R1, Gemma 3 & Reasoning LLMs 2x faster with 70% less memory! 🦥
Use PEFT or Full-parameter to CPT/SFT/DPO/GRPO 500+ LLMs (Qwen3, Qwen3-MoE, Llama4, InternLM3, GLM4, Mistral, Yi1.5, DeepSeek-R1, ...) and 200+ MLLMs (Qwen2.5-VL, Qwen2.5-Omni, Qwen2-Audio, Ovis2, InternVL3, Llava, MiniCPM-V-2.6, GLM4v, Xcomposer2.5, DeepSeek-VL2, Phi4, GOT-OCR2, ...).
Open Source Deep Research Alternative to Reason and Search on Private Data. Written in Python.
A native macOS app that allows users to chat with a local LLM that can respond with information from files, folders and websites on your Mac without installing any other software. Powered by llama.cpp.
Rushikesh Nimkar's portfolio, accessible at rushikeshnimkar.xyz, is a modern website built with Next.js 15 and TypeScript. It features AI-powered email generation, an interactive chat with an AI version of Rushikesh, dynamic animations, responsive design, dark mode, and showcases his projects and contributions.
Combining OCR for text extraction with LLMs for accurate, efficient document structuring.
A powerful Python tool for supercharging search with generative AI. Create SGE-optimized content, analyze intent, generate schema, and optimize SERP features—all in one platform.
analisi de repositirios, en el que podras ver distintos tipos de diagramas, analisis de vulnerabilidades, issues, con la api de huggingFace se usa LLama4 para hacerle preguntas al modelo sobre el repositorio y el estatus del proyecto, tienes la opcion de agregar distintos tipos de roles y personalidad
This project demonstrates three progressively advanced approaches to converting unstructured data into structured formats using AI
AlphaExtract is a sophisticated PDF summarization tool that combines cutting-edge AI technology with efficient document processing. The project is built using Python and leverages Meta's LLaMA 4 MOE Maverick model along with Groq's inference engine to provide fast and accurate PDF summaries.
Add a description, image, and links to the llama4 topic page so that developers can more easily learn about it.
To associate your repository with the llama4 topic, visit your repo's landing page and select "manage topics."