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. -
BigScience
BLOOM
FREEBigScience Large Open-science Open-access Multilingual Language Model (BLOOM) is a transformer-based LLM. Over 1,000 AI researchers created it to provide a free large language model for everyone who wants to try and it is a multilingual LLM. BLOOM is an autoregressive Large Language Model (LLM), trained to continue text from a prompt on vast amounts of text data using industrial-scale computational resources. It can output coherent text in 46 languages and 13 programming languages. It is free, and everybody who wants to can try it out. To interact with the API, you’ll need to request a token. This is done with a post request to the server. Tokens are only valid for two weeks. After which, a new one must be generated. Trained on around 176B parameters, it is considered an alternative to OpenAI models. There is a downloadable model, and a hosted API is available. -
OpenAI
Claude 2 (Web Browser Version)
FREEAnthropic’s Claude 2 is now available to the public if you’re in the US or UK. For the web browser version. just click “Talk to Claude,” and you’ll be prompted to provide an email address. After you confirm the address you enter, you’ll be ready to go.Claude 2 scored 76.5 percent on the multiple choice section of the Bar exam and in the 90th percentile on the reading and writing portion of the GRE. Its coding skills have improved from its predecessor scoring 71.2 percent on a Python coding test compared to Claude’s 56 percent. While the Google-backed Anthropic initially launched Claude in March, the chatbot was only available to businesses by request or as an app in Slack. With Claude 2, Anthropic is building upon the chatbot’s existing capabilities with a number of improvements. -
NVIDIA
LaunchPad
FREENVIDIA LaunchPad provides free access to enterprise NVIDIA hardware and software through an internet browser. NVIDIA customers can experience the power of AI with end-to-end solutions through guided hands-on labs or use NVIDIA-Certified Systems as a sandbox, but you need to fill out an Application Form and wait for approval. Sample labs include training and deploying a support chatbot, deploying an end-to-end AI workload, configuring and deploying a language model on the hardware accelerator, and deploying a fraud detection model.*FREE via Application Form -
Microsoft, NVIDIA
MT-NLG
OTHERMT-NLG (Megatron-Turing Natural Language Generation) uses the architecture of the transformer-based Megatron to generate coherent and contextually relevant text for a range of tasks, including completion prediction, reading comprehension, commonsense reasoning, natural language inferences, and word sense disambiguation. MT-NLG is the successor to Microsoft Turing NLG 17B and NVIDIA Megatron-LM 8.3B. The MT-NLG model is three times larger than GPT-3 (530B vs 175B). Following the original Megatron work, NVIDIA and Microsoft trained the model on over 4,000 GPUs. NVIDIA has announced an Early Access program for its managed API service to the MT-NLG model for organizations and researchers. -
NVIDIA
NeMo
FREENVIDIA NeMo, part of the NVIDIA AI platform, is an end-to-end, cloud-native enterprise framework to help build, customize, and deploy generative AI models. NeMo makes generative AI model development easy, cost-effective and fast for enterprises. NeMo has separate collections for Automatic Speech Recognition (ASR), Natural Language Processing (NLP), and Text-to-Speech (TTS) models. Each collection consists of prebuilt modules that include everything needed to train on your data. NeMo framework supports both language and image generative AI models. Currently, the workflow for language is in open beta, and the workflow for images is in early access. You must be a member of the NVIDIA Developer Program and logged in with your organization’s email address to access it. It is licensed under the Apache License 2.0, which is a permissive open source license that allows for commercial use. -
LMSYS Org
Vicuna-13B
FREEVicuna-13B is an open-source chatbot developed by a team of researchers from UC Berkeley, CMU, Stanford, MBZUAI, and UC San Diego. The chatbot was trained by fine-tuning LLaMA on user-shared conversations collected from ShareGPT. There is a 13B and 7B parameter models that are available on Hugging Face.
Vicuna-13B achieves more than 90% quality of OpenAI ChatGPT and Google Bard while outperforming other models like LLaMA and Stanford Alpaca in more than 90% of cases. The code and weights and an online demo are publicly available for non-commercial use. Here is a link to learn more about how it compares to other models – https://lmsys.org/blog/2023-03-30-vicuna/.
To use this model, you need to install LLaMA weights first and convert them into Hugging Face weights, and the cost of training Vicuna-13B is around $300.
