One Line LLM Tuner
Fine-tune any Hugging Face LLM in one line
Listed in categories:
Developer ToolsGitHubArtificial Intelligence
Description
One Line LLM Tuner is a Python package designed to simplify the process of finetuning large language models (LLMs) like GPT2, Llama2, GPT3, and more. With just one line of code, you can finetune a pretrained model to your specific dataset, acting as a wrapper for the transformers library, similar to how Keras works for TensorFlow.
How to use One Line LLM Tuner?
After installing the package using pip, you can finetune a model by importing the llmtuner and using the FineTuneModel class to specify your training and testing datasets, along with other parameters.
Core features of One Line LLM Tuner:
1️⃣
Simple finetuning with minimal code
2️⃣
Supports popular LLMs from the transformers library
3️⃣
Customizable finetuning process for advanced users
4️⃣
Easy installation via pip
5️⃣
Single line code execution for model finetuning
Why could be used One Line LLM Tuner?
| # | Use case | Status | |
|---|---|---|---|
| # 1 | Finetuning GPT-2 for specific text generation tasks | ✅ | |
| # 2 | Customizing LLMs for domain-specific applications | ✅ | |
| # 3 | Rapid prototyping of language models with minimal setup | ✅ | |
Who developed One Line LLM Tuner?
The One Line LLM Tuner is created by Suhas Bhairav, who aims to simplify the process of working with large language models through efficient coding practices.