ChatGPT and GPT-4 Open Source Alternatives that are Balancing the Scale
GPT-4 is a leading Generative AI developed by OpenAI. However, it is not open-source, meaning users don’t have access to the code, model architecture, data, or model weights to reproduce the results. To balance the scale, open-source communities are developing GPT-4 alternatives that offer almost similar performance and functionality, but require fewer computational resources.
Here are 12 GPT-4 alternatives with a brief description and links to the relevant research paper, blog post, chatbot demo, code source, and model card:
1. ColossalChat
ColossalChat is an open-source project that allows users to clone AI models using a complete RLHF (Reinforcement Learning from Human Feedback) pipeline. The project comprises a bilingual dataset, training code, demo, and 4-bit quantized inference. All the components will help users create a customized chatbot cheaper and faster.
2. Alpaca-LoRA
Alpaca-LoRA is a model created using the Stanford Alpaca and low-rank adaptation (LoRA). The low-rank adoption allows us to run an Instruct model of similar quality to GPT-3.5 on 4GB RAM Raspberry Pi 4. The project provides source code, fine-tuning examples, inference code, model weights, dataset, and demo. Users can train their model within a few hours on a single RTX 4090.
3. Vicuna
Vicuna can generate coherent and creative text for chatbots. It is a transformer-based architecture fine-tuned on a conversational dataset collected from ShareGPT.com. Vicuna provides almost 90% of ChatGPT performance and is a part of the open platform, FastChat, which allows users to train, serve, and evaluate their chatbots.
4. GPT4ALL
GPT4ALL is a chatbot developed by the Nomic AI Team on massive curated data of assisted interaction like word problems, code, stories, depictions, and multi-turn dialogue. The model architecture is based on LLaMa and uses low-latency machine-learning accelerators for faster inference on the CPU. With GPT4ALL, users get a Python client, GPU and CPU interference, Typescript bindings, a chat interface, and a Langchain backend.
5. Raven RWKV
Raven RWKV is part of ChatRWKV, an open-source model like ChatGPT but powered by RWKV (100% RNN) language model, not transformer-based. By utilizing RNNs, the model achieves comparable levels of quality and scalability as transformers, with the added benefits of faster processing speed and VRAM conservation. Raven was fine-tuned to follow instructions and was fine-tuned on Stanford Alpaca, code-alpaca, and more datasets.
6. OpenChatKit
OpenChatKit is a comprehensive toolkit that offers an open-source alternative to ChatGPT for developing the chatbot application. The toolkit includes step-by-step instructions for training your instruction-tuned large language model, fine-tuning the model, and an extensible retrieval system for updating the bot's responses. Additionally, it includes both moderation features that can help filter out inappropriate questions.
7. OPT (Open Pre-trained Transformer) Language Models
OPT Language Models have demonstrated remarkable abilities in zero-shot and few-shot learning, as well as Stereotypical Bias analysis, despite not matching the quality of ChatGPT. OPT is a family of large language models ranging from 125M to 175B parameters. The models are decoder-only transformers, which means they generate text autoregressive from left to right.
8. Flan-T5-XXL
Flan-T5-XXL was fine-tuned T5 models trained on a vast collection of datasets presented in the form of instructions. This fine-tuning has significantly improved performance on a variety of model classes, such as PaLM, T5, and U-PaLM. Moreover, the Flan-T5-XXL model was fine-tuned on more than 1000 additional tasks covering multiple languages.
9. Baize
Baize exhibits impressive performance in multi-turn dialogues thanks to its guardrails that help mitigate potential risks. It has achieved this through a high-quality multi-turn chat corpus, which was developed by leveraging ChatGPT to facilitate conversations with itself. Baize code source, model, and dataset are released under a non-commercial (research purposes) license.
10. The Koala
The Koala is a chatbot trained by fine-tuning LLaMa on a dialogue dataset scraped from the web. Koala has performed better than Alpaca and is similar to ChatGPT in many cases. Koala provides training code, public weights, and dialogue fine-tuner and was evaluated by 100 humans.
11. Dolly
Dolly is a large language model trained by Databricks machine to demonstrate that we can use old open-source language model and give them ChatGPT magic instruction-following ability. The model training requires 30 minutes on one machine, using high-quality training data. You don’t even require large models to achieve high quality. The team has used the 6 billion parameters model, compared to 175 billion for GPT-3.
12. Open Assistant
Open Assistant is a truly open-source project that aims to create a revolution in innovation in language by enabling people to interact with third-party systems, retrieve information dynamically, and create new applications using language. Users can run the large language chatbot on a single high-end consumer GPU, and its code, models, and data are licensed under open-source licenses.
These GPT-4 alternatives provide researchers, developers, and small companies the opportunity to create their language-based technology and compete with industry giants. Their performance is not above GPT-4, but with time and community contribution, some could have the potential to overtake GPT-4. If you are new to ChatGPT, you can take our Introduction to ChatGPT course or review the comprehensive ChatGPT Cheat Sheet for Data Science to get better at prompting.
