Large AI models and applications, such as ChatGPT and GPT-4, have become increasingly popular worldwide, with many experts from academia and industry joining the entrepreneurial wave of technology development. Generative AI continuously improves, and technology giants are racing to release new products to capitalize on its potential.
However, the lack of open-source models has left many curious about the technical details behind these models. Individuals can turn to open-source solutions such as Colossal-AI to stay current and participate in the wave of technology development.
Colossal-AI is the leading open-source large AI model solution with a complete RLHF pipeline open-sourced. The pipeline includes:
- Supervised data collection.
- Supervised fine-tuning.
- Reward model training.
- Reinforcement learning fine-tuning based on the LLaMA pre-trained model.
The solution also includes the ColossalChat open-source project, resembling the original ChatGPT technical solution.
The open-source solution provided by Colossal-AI includes an interactive demo that can be used online without registration or joining a waiting list. The demo offers a hands-on experience to help users understand the technology’s work.
The training code provided by Colossal-AI is open-source and complete, including 7B and 13B models. The open-source 104K bilingual dataset of Chinese and English is also available, which can be used to train the models. This dataset can be used to create more accurate and robust models.
The inference provided by Colossal-AI is 4-bit quantized, allowing seven billion-parameter models to require only 4GB of GPU memory. This can reduce the cost of building and applying large AI models. The model weights provided by Colossal-AI enable quick reproduction with only a tiny amount of computing power on a single server. This allows individuals to run large AI models without expensive hardware on their computers or laptops.
Open-source solutions such as Colossal-AI can help lower the high cost of building and applying large AI models. These solutions provide individuals with the necessary tools and datasets to build their AI models. They also offer a way for individuals to contribute to the development of the technology and improve its accuracy and robustness.
One of the concerns with using third-party large model APIs is the risk of data and intellectual property being leaked. Using open-source solutions, individuals can protect their core data and IP from being leaked through third-party APIs.
In conclusion, the lack of open-source models has left many curious about the technical details behind large AI models such as ChatGPT and GPT-4. Open-source solutions such as Colossal-AI provide individuals with the necessary tools and datasets to build their AI models. These solutions can help lower the high cost of building and applying large AI models, protect core data and IP, and provide a way for individuals to contribute to the development of the technology. As the technology continues to improve, open-source solutions will play a vast and increasingly important role in democratizing access to large AI models and making the technology accessible to a broader audience.
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Niharika is a Technical consulting intern at Marktechpost. She is a third year undergraduate, currently pursuing her B.Tech from Indian Institute of Technology(IIT), Kharagpur. She is a highly enthusiastic individual with a keen interest in Machine learning, Data science and AI and an avid reader of the latest developments in these fields.