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xTuring

Discover xTuring, the open-source AI library for personalizing and fine-tuning Large Language Models with ease and efficiency.

Natural Language Processing Updated 13 minutes ago

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xTuring's Top Features

Open-source

Easy-to-use interface

Supports LoRA, INT8, INT4 precisions

Efficient compute and memory usage

Customizable AI models

Supports a wide range of LLMs

Community support through Discord and Twitter

Detailed documentation and quick start guides

Editable installation for contributions

Licensed under Apache 2.0

Frequently asked questions about xTuring

Refer to our tutorial on fine-tuning any model of your choice. The list of supported models can be found on our website.

You can follow our guide on how to load any other model of your choice that is not listed in the supported models.

Yes, you can. We have a tutorial that demonstrates how to load the Alpaca Dataset and prepare it for instruction fine-tuning.

To contribute to xTuring, you need to do an editable install of the source code on your machine. The setup steps are available on our website.

xTuring supports LoRA, 8-bit precision, LoRA with 8-bit precision, and LoRA with 4-bit precision techniques for memory-efficient fine-tuning.

Ensure you have Python 3.0+, create a virtual environment, activate it, and run 'pip install xTuring' to install the library.

Yes, create a Conda environment with 'conda create -n venv', activate it, and run 'pip install xTuring' to install the library.

Run the following commands in the terminal: 'python', 'from xturing.models import BaseModel', 'model = BaseModel.create("opt")', 'outputs = model.generate(texts=["Hi How are you?"])', and then print the outputs to see the generated text.

Refer to the installation guide on our website, ensuring you meet all prerequisites such as Python 3.0+ and virtual environment setup.

Join our Discord community and follow us on Twitter @stochasticai for support and updates.

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xTuring

xTuring's Top Features

Frequently asked questions about xTuring

How do I fine-tune a Large Language Model (LLM) with xTuring?

What if the model I want to use isn't in the supported models list?

Can I use an existing dataset for instruction fine-tuning?

How do I set up xTuring to start contributing?

What fine-tuning techniques does xTuring support?

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Can I install xTuring using Conda?

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What should I do if I encounter issues during installation?

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