Step-by-Step Neural Network Training
Join Andrej Karpathy for a step-by-step guide on neural network training and backpropagation. Understand the core concepts and implement them in Python.
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Python
Qwen-2: Master Function Calling and Agents
Explore Alibaba’s Qwen-2 model’s function calling and agentic workflows. Learn to set up and run Qwen-2 locally, create custom agents, and understand quantization impacts.
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Chat with Knowledge Graph using LLMs
Geraldus Wilsen’s tutorial explains integrating knowledge graphs with LLMs using Python, Neo4J, Langchain, and Gemini. Enhance your model’s performance with these techniques.
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Python Bindings for Llama.cpp Library
Utilize Python bindings for llama.cpp to enhance your projects with efficient hardware acceleration, detailed documentation, and OpenAI compatibility.
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vLLM, the efficient LLM serving library
Discover vLLM, the efficient LLM serving library. A fast, flexible, and user-friendly tool for LLM inference and serving.
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Streamlit App Framework: Tutorial and Deployment Guide
Create and share beautiful web apps for data science and machine learning quickly with Streamlit. No front-end experience needed, deploy instantly for free.
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