《动手学大模型Dive into LLMs》系列编程实践教程

A comprehensive guide and codebase for text summarization using Large Language Models (LLMs). Dive into techniques, from chunking to clustering, and harness the power of LLMs like GPT-3.5 and GPT-4.

Comparing the Performance of LLMs: A Deep Dive into Roberta, Llama, and Mistral for Disaster Tweets Analysis with Lora

🔎 A deep-dive into HyDE for Advanced LLM RAG + 💡 Introducing AutoHyDE, a semi-supervised framework to improve the effectiveness, coverage and applicability of HyDE

Dive into the Foundations of LLMs, System Design Strategies, and the Latest Tools & Updates in Generative AI.

Learn the ins and outs of efficiently serving Large Language Models (LLMs). Dive into optimization techniques, including KV caching and Low Rank Adapters (LoRA), and gain hands-on experience with Predibase’s LoRAX framework inference server.

:star: Dive into LLM Agents

✍️ Dive into this repository to explore a treasure trove of code examples, showcasing various methods and approaches for working with LLMs. These examples are inspired by my own learning journey and personal experiences, designed to ignite your passion for AI and machine learning.

Exploiting LLM overreach to delete users via prompt engineering — a deep dive into PortSwigger’s excessive agency lab.

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The official github repo for the open online courses: "Dive into LLMs".

Deep Dive into Large Language Models (LLMs) – A comprehensive study of Large Language Models, from their inner workings and architecture to their applications, challenges, and future.

Weaponizing LLM prompt injection to hijack user deletion logic — an offensive deep dive into excessive agency abuse.

Explore practical fine-tuning of LLMs with Hands-on Lora. Dive into examples that showcase efficient model adaptation across diverse tasks.

Explore the realms of graph databases with Neo4j, dive into Cypher queries, and integrate LLMs for dynamic data insights with Langchain. A personal journey to master graph data.

Explore the potential of Large Language Models (LLMs) for network security through real-time analysis and categorization of DNS queries. This project uses OpenAI's API to monitor network traffic within a home network environment, emphasizing ethical practices and privacy. Dive into the code to see how AI can enhance network visibility and security.

This example repository illustrates the usage of LLMs with Quarkus by using the quarkus-langchain4j extension to build integrations with ChatGPT or Hugging Face. The code dives into simple conversations, retrieval augmented generation (RAG) and building agents.

Deep dives into LLM post-training (RLHF/RLVR) and agentic reinforcement learning.

30-Days-LLM-Mastery-Course: A comprehensive, hands-on course diving deep into Large Language Models (LLMs). From foundational concepts to advanced techniques, learn to build, train, and deploy state-of-the-art language models.

Diving into Prompt Engineering for LLMs within this repository. Learning and practicing the latest techniques and methods through practical examples to gain working knowledge in this ever-growing technology..

This project focuses on text-generation LLMs, offering a deep dive into building and fine-tuning large language models for generating human-like text. It covers key techniques in training, prompt engineering, and model optimization, enabling the creation of powerful, context-aware text generation applications for diverse use cases.

Focused on NLP and AI, currently diving deep into Large Language Models (LLMs) that revolutionize human language understanding and generation.

Crafting ML solutions for healthcare & finance, specializing in LLMs, computer vision, and NLP. Feel free to dive into my repositories and reach out for collaborations—I’m all about bridging the gap between academic research and industry impact.

Research artifacts exploring Search-based vs. Agentic RAG strategies for AI Code Review. A deep dive into solving the "Context Instability" problem in LLM-based software engineering, analyzing trade-offs in recall, latency, and cost.

Diving into LLMs like they're a grimoire

Dive into the world of LLM Guardrails using tools like NVIDIA’s NeMo Guardrails. Discover the mechanisms that ensure applications produce reliable, robust, safe, and ethical outputs, and understand their crucial role in LLMs

A deep dive into where, how, and why activation steering works (or doesn't) on instruction-tuned LLMs

Dive into LLM development! Learn cutting-edge techniques behind models like OpenAI's GPT-4, Meta's LLaMA 2, Mistral-7B, and Anthropic's Claude. Master PyTorch, build transformers, & fine-tune pre-trained LLMs from Hugging Face.

Exploring the Falcon LLM Series: A deep dive into one of the leading open-source model families, their architecture, benchmarks, and practical applications, including an interactive demo.