awesome-LLM-resources

A comprehensive collection of global large language model resources.

CommonProductProductivityLarge Language ModelsResource Aggregation

awesome-LLM-resources is a platform that aggregates global resources for large language models (LLMs), offering a range of tools and resources from data acquisition and fine-tuning to inference, evaluation, and real-world applications. Its significance lies in providing researchers and developers with a comprehensive resource library to facilitate the efficient development and optimization of their language models. Maintained by Wang Rongsheng, the platform is continuously updated, providing robust support for the advancement of the LLM field.

Offers methods for large-scale data acquisition and processing
such as tools like AutoLabel and LabelLLM.
Aggregates various fine-tuning frameworks and libraries
including LLaMA-Factory and unsloth.
Includes multiple inference engines and libraries
such as ollama and Open WebUI.
Provides tools and platforms for evaluating language model performance
such as lm-evaluation-harness and opencompass.
Summarizes practical application cases and experience platforms
like LMSYS Chatbot Arena and CompassArena.

\The target audience includes researchers in natural language processing
machine learning engineers
data scientists
and developers interested in large language models. These resources can assist them in quickly acquiring necessary data
selecting appropriate fine-tuning frameworks

Researchers clean and enrich text datasets using the AutoLabel tool.
Developers utilize the LLaMA-Factory framework to fine-tune models for specific tasks.
Businesses evaluate the performance of different language models through the CompassArena platform
selecting the most suitable model for deployment in their products.

1. Visit the awesome-LLM-resources website to browse various resources and tools.
2. Select the appropriate data acquisition
fine-tuning
inference
or evaluation tools based on your needs.

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