LLM resources
For generative pre trained transformer lists, the strongest matches are dair-ai/prompt-engineering-guide (This repository is a curated educational guide providing comprehensive), microsoft/generative-ai-for-beginners (This repository provides a structured educational curriculum and learning) and rasbt/llm-architecture-gallery (This repository provides structured source data on various LLM). rohitg00/awesome-ai-apps is also worth a look. Each is ranked by relevance to your query, popularity and recent activity.
Hand-picked generative pre-trained transformer repositories, ranked by GitHub stars and activity. Compare the top LLM resources and pick the right one.
LLM resources
Trouvez les meilleurs dépôts grâce à l'IA.Nous recherchons les dépôts les plus pertinents grâce à l'IA.
- dair-ai/prompt-engineering-guide
dair-ai/Prompt-Engineering-Guide
75,678Voir sur GitHubThis project is a comprehensive educational resource and technical guide focused on the development, optimization, and application of large language models. It provides a structured curriculum for mastering prompt engineering, ranging from foundational principles of instruction design to advanced techniques for improving model reasoning, accuracy, and reliability. The guide distinguishes itself by offering deep technical insights into agentic workflows and autonomous system design. It covers the implementation of multi-step reasoning chains, tool integration through function calling, and stat
This repository is a curated educational guide providing comprehensive resources on prompt engineering, agentic workflows, and large language model applications, matching your search for curated LLM materials.
MDXPrompt EngineeringPrompt EngineeringModel Evaluation - microsoft/generative-ai-for-beginners
microsoft/generative-ai-for-beginners
112,045Voir sur GitHubThis project is a comprehensive, open-source educational curriculum designed to guide developers through the mastery of generative artificial intelligence. It provides a structured learning path that covers foundational concepts, prompt engineering, and the practical application of large language models. The repository serves as a central hub for skill acquisition, offering sequential modules that progress from basic model mechanics to advanced architectural patterns. The curriculum distinguishes itself by focusing on the end-to-end lifecycle of intelligent software, including the implementat
This repository provides a structured educational curriculum and learning path for generative AI, featuring prompt engineering and application guides, though it functions as a learning resource rather than a raw list of papers or models.
Jupyter NotebookModel Fine-Tuning GuidesAdvanced Prompting TechniquesModel Benchmarking - rasbt/llm-architecture-gallery
rasbt/llm-architecture-gallery
1,305Voir sur GitHubThe llm-architecture-gallery is a structured catalog and reference platform for exploring machine learning model architectures. It maintains a curated directory of language model specifications, release dates, parameter counts, and technical fact sheets. The platform includes a dedicated comparison tool that aligns model attributes side by side to evaluate structural differences, design tradeoffs, and attention mechanisms. Users can browse the reference collection and analyze aggregated metadata across various architectures. Underlying data is maintained in structured YAML files and process
This repository provides structured source data on various LLM architectures, which aligns with the request for curated resources on model architectures, though it lacks some of the broader guides and tools in this category.
Language Model ArchitecturesArchitecture Metadata ManagementArchitecture Reference Directories - rohitg00/awesome-ai-apps
rohitg00/awesome-ai-apps
This project serves as a curated directory and resource hub for developers working with generative artificial intelligence. It provides a comprehensive index of open-source software solutions, frameworks, and project examples designed to help users discover and implement advanced AI systems. The repository focuses on practical implementations of agentic, multimodal, and retrieval-augmented generation architectures. It highlights tools for building conversational assistants, voice-enabled agents, and automated workflows that leverage large language models. By showcasing diverse technical domai
This project serves as a curated directory of generative AI applications and frameworks, making it a relevant resource hub for the requested topic, though it emphasizes application examples over academic papers and foundational models.
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