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Finetune Llama 4, DeepSeek-R1, Gemma 3 & Reasoning LLMs 2x faster with 70% less memory! 🦥
Efficient Triton Kernels for LLM Training
An efficient, flexible and full-featured toolkit for fine-tuning LLM (InternLM2, Llama3, Phi3, Qwen, Mistral, ...)
This is a Phi Family of SLMs book for getting started with Phi Models. Phi a family of open sourced AI models developed by Microsoft. Phi models are the most capable and cost-effective small language models (SLMs) available, outperforming models of the same size and next size up across a variety of language, reasoning, coding, and math benchmarks
An open-source project for Windows developers to learn how to add AI with local models and APIs to Windows apps.
🔥🔥 LLaVA++: Extending LLaVA with Phi-3 and LLaMA-3 (LLaVA LLaMA-3, LLaVA Phi-3)
[ICLR 2025] Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing. Your efficient and high-quality synthetic data generation pipeline!
Instruction/chat prompts creation library for text generation LLMs. It supports local and Hugging Face models.
Generative AI playground using Ollama, OpenAI API and JavaScript. Try AI models in your browser!
This experiment repository will be used for demonstration on using Phi-3.5, Microsoft's Small Language Model, locally with Ollama and JavaScript for the event of BKK.JS #21 and JavaScript Bangkok 2.0.0
A RAG system is just the beginning of harnessing the power of LLM. The next step is creating an intelligent Agent. In Agentic RAG the Agent makes use of available tools, strategies and LLM to generate response in a specialized way. Unlike a simple RAG, an Agent can dynamically choose between tools, routing strategy, etc.
Access 41K+ serverless AI models across 33+ ML tasks with a unified schema. Run fast, affordable inference in seconds through a simple API ✨
Sentiment analysis with pre-trained language models using TweetEval.
