Compare Models
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Stanford University
Alpaca
FREEStanford University released an instruction-following language model called Alpaca, which was fine-tuned from Meta’s LLaMA 7B model. The Alpaca model was trained on 52K instruction-following demonstrations generated in the style of self-instruct using text-davinci-003. Alpaca aims to help the academic community engage with the models by providing an open source model that rivals OpenAI’s GPT-3.5 (text-davinci-003) models. To this end, Alpaca has been kept small and cheap (fine-tuning Alpaca took 3 hours on 8x A100s which is less than $100 of cost) to reproduce. All training data and techniques have been released. The Alpaca license explicitly prohibits commercial use, and the model can only be used for research/personal projects, and users need to follow LLaMA’s license agreement. -
BloombergGPT
BloombergGPT
OTHERBloombergGPT represents the first step in developing and applying LLM and generative AI technology for the financial industry. Bloomberg GPT has been trained on enormous amounts of financial data and is purpose-built for finance. The mixed dataset training leads to a model that outperforms existing LLMs on financial tasks by significant margins without sacrificing performance on general LLM benchmarks. Bloomberg GPT can perform a range of NLP tasks such as sentiment analysis, named entity recognition, news classification, and even writing headlines. With Bloomberg GPT, traders and analysts can perform financial analysis and insights more quickly and efficiently, saving valuable time that can be used for other critical tasks. To use Bloomberg GPT, you need access to Bloomberg’s terminal software (a platform investors and financial professionals use to access real-time market data, breaking news, financial research, and advanced analytics). Bloomberg also offers a variety of other subscription options, including subscriptions for financial institutions, universities, and governments. The price of a Bloomberg terminal varies depending on the type of subscription and the number of users. -
Deepmind
Chinchilla AI
OTHERGoogle’s DeepMind Chinchilla AI is still in the testing phase. Once released, Chinchilla AI will be useful for developing various artificial intelligence tools, such as chatbots, virtual assistants, and predictive models. It functions in a manner analogous to that of other large language models such as GPT-3 (175B parameters), Jurassic-1 (178B parameters), Gopher (280B parameters), and Megatron-Turing NLG (300B parameters) but because Chinchilla is smaller (70B parameters), inference and fine-tuning costs less, easing the use of these models for smaller companies or universities that may not have the budget or hardware to run larger models.
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StableLM
StableLM-Base-Alpha -7B
FREEStability AI released a new open-source language model, StableLM. The Alpha version of the model is available in 3 billion and 7 billion parameters. StableLM is trained on a new experimental dataset built on The Pile, but three times larger with 1.5 trillion tokens of content. The richness of this dataset gives StableLM surprisingly high performance in conversational and coding tasks, despite its small size. The models are now available on GitHub and on Hugging Face, and developers can freely inspect, use, and adapt our StableLM base models for commercial or research purposes subject to the terms of the CC BY-SA-4.0 license.
