Xturing

What is Xturing?

Xturing Xturing is an open-source AI personalization library designed to simplify the process of building and controlling large language models. It offers a user-friendly interface for fine-tuning models and generating datasets from user data sources. Xturing Xturing supports various models such as LLaMA, GPT-J, GPT-2, OPT, Cerebras-GPT, Galactica, and Bloom. The tool is accessible to both novices and experienced developers, providing a balance between ease of use and customization options.

Furthermore, the team behind Xturing Xturing aims to make AI easier to use and more helpful for everyone. They come from diverse backgrounds with expertise in areas like machine learning, computers, and real-life AI applications. The core principles guiding Xturing Xturing 's development include simplicity and productivity, efficiency of compute and memory, as well as agility and customizability. The team is committed to supporting users in utilizing AI effectively in the evolving landscape of technology.

Who created Xturing?

Xturing was created by a team from Stochastic with a shared goal of democratizing AI access. The platform was launched on June 17, 2024. The team consists of various experts in AI research and engineering distributed globally, working together to simplify AI usage and innovation. Xturing aims to make AI user-friendly and powerful for all, emphasizing simplicity, efficiency, and customizability in AI model development.

What is Xturing used for?

• Fine-tuning models to match specific needs or application requirements
• Generating datasets from data sources
• Evaluating modified models
• Model saving and loading
• Inference capabilities
• Preparing and saving datasets
• Support for multiple large language models
• Customizing AI models
• Building chatbots (implied)
• Contributing to the xTuring project
• Fine-tuning LLaMA on Alpaca dataset
• Fine-tuning GPT-J with/without INT8
• Fine-tuning Cerebras-GPT on Alpaca dataset with/without LoRA and with/without INT8
• Fine-tuning GPT-2 on Alpaca dataset with/without LoRA and with/without INT8
• Fine-tuning Falcon 7B on Alpaca dataset with/without LoRA and with/without INT8
• Fine-tuning Galactica on Alpaca dataset with/without LoRA and with/without INT8
• Fine-tuning Generic Wrapper large language model on Alpaca dataset with/without LoRA and with/without INT8
• Fine-tuning LLaMA 7B on Alpaca dataset with/without LoRA and with/without INT8
• Fine-tuning LLaMA 2 7B on Alpaca dataset with/without LoRA and with/without INT8
• Fine-tuning OPT on Alpaca dataset with/without LoRA and with/without INT8

Who is Xturing for?

• Developers
• Users with varying levels of AI knowledge

How to use Xturing?

To use Xturing, follow these steps:

1. Understanding Xturing: Xturing is an open-source AI personalization library designed to simplify the building and customization of large language models.

2. Compatibility with Various Models: Xturing supports a range of models including LLaMA, GPT-J, GPT-2, OPT, Cerebras-GPT, Galactica, and Bloom.

3. User Accessibility: Xturing is user-friendly, catering to both beginners and experienced developers. It offers a Quickstart guide to assist users in getting started.

4. Fine-Tuning Models: Utilize the fine-tuning feature to optimize model performance for specific needs and applications. Examples include fine-tuning on Alpaca dataset with/without LoRA and with/without INT8.

5. Installation: Install Xturing easily using the pip install command. Detailed installation instructions are available on their website.

6. Customization of AI Models: Xturing allows users to customize AI models by adjusting the models to tailor to specific requirements.

7. Dataset Generation: Generate datasets from data sources through the user-friendly interface following the 'Prepare and save dataset' guide in the Quickstart section on the website.

8. Evaluation of Models: Evaluate modified models using Xturing to assess their performance in alignment with your needs or application requirements.

Xturing ensures efficient computing and memory utilization and is licensed under Apache 2.0, promoting community involvement and transparency. For further details, refer to the documentation and resources available on the Xturing website.