This video introduces GPTO OSS, OpenAI's new open-source large language model, highlighting its free, private, and customizable nature. It details two versions: a small version compatible with high-end GPUs and a large version requiring an H100 GPU or remote inference via Hugging Face. The video provides a quick guide for local setup, including necessary software installations, and explains how to access the large model remotely using a Hugging Face token. It emphasizes the model's customization capabilities, such as altering its identity, fine-tuning, accessing its chain of thought, and quantizing it for less powerful hardware, concluding with an anticipation of customized models becoming available on Hugging Face soon.
Key Features of GPTO OSS and Setup Guide:
0:00 Introduction to GPTO OSS: OpenAI's new open-source model, emphasized as free, private, and fully customizable.
0:06 Model Versions: Available in a small version (runs on high-end GPUs) and a large version (requires an H100 GPU).
0:10 Local Setup: Instructions provided to run locally by installing Python, pivotal-transformers, and accelerate-kernels, followed by a specific script.
0:17 Remote Access (Large Model): The large model can be run remotely using Hugging Face Inference Providers, which is a paid service but retains privacy and customizability.
0:19 Hugging Face Token Requirement: To access the large model remotely, a Hugging Face 'read' access token is necessary and should be stored in environment variables.
0:31 Customization Options: Users can customize the model by changing its identity, fine-tuning it, reading its "chain of thought," or quantizing it to run on lower-end GPUs.
0:42 Future Availability: Customized versions of GPTO OSS models are expected to be available on Hugging Face very soon.