awesome-LLM-resources

🥇Gold

A curated list of the world's best LLM resources for operations teams. It covers multimodal generation, agents, coding assistance, AI proofreading, data processing, model training, and inference. Connects to Claude for enhanced workflows.

7,5677230Updated Today

Intermediate30min to implementautomation

Saves ~10 min per use

Quick InstallView Source

git clone https://github.com/WangRongsheng/awesome-LLM-resources.git

Works with:

Claude

Overview

About This Skill

https://github.com/WangRongsheng/awesome-LLM-resourses

Use Cases

Automate the process of fine-tuning language models with curated datasets.

Utilize multimodal generation techniques to create diverse content types.

Implement agent-based systems for task automation in software development.

Extract and process large datasets efficiently for training LLMs.

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/WangRongsheng/awesome-LLM-resources

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

Summarize the top resources for [TOPIC] related to LLMs, including [SPECIFIC_AREAS_OF_INTEREST]. Provide a brief overview of each resource, highlighting its key features and how it can be beneficial for [TARGET_AUDIENCE].

Example Output

1. **Hugging Face Transformers**: A comprehensive library for natural language processing that provides pre-trained models and tools for fine-tuning. Ideal for developers looking to implement state-of-the-art LLMs in their applications. Key features include easy integration with PyTorch and TensorFlow, along with extensive documentation and community support.

2. **OpenAI API**: Offers access to powerful language models for various applications such as chatbots and content generation. Users can leverage its capabilities through a simple API, making it suitable for businesses aiming to enhance customer engagement with AI-driven solutions.

3. **Google AI’s T5**: A transformer-based model that excels in text-to-text tasks. This resource is particularly beneficial for researchers and developers interested in multi-task learning and transfer learning. It provides a unified framework for handling diverse NLP tasks, which can significantly reduce development time.

4. **Papers with Code**: A platform that connects research papers with their implementations. For those in academia or industry, this resource is invaluable for staying updated on the latest advancements in LLMs and finding practical implementations to build upon.

5. **EleutherAI’s GPT-Neo**: An open-source alternative to proprietary models, this resource allows users to experiment with large language models without the associated costs. It's perfect for startups and researchers looking to innovate without heavy financial investment.