Compare Models
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Google, Stanford University
Electra
FREEELECTRA (Efficiently Learning an Encoder that Classifies Token Replacements Accurately) is a transformer-based model like BERT, but it uses a different pre-training approach, which is more efficient and requires less computational resources. It was created by a team of researchers from Google Research, Brain Team, and Stanford University. ELECTRA models are trained to distinguish “real” input tokens vs “fake” input tokens generated by another neural network (for the more technical audience, ELECTRA uses a new pre-training task, called replaced token detection (RTD), that trains a bidirectional model while learning from all input positions). Inspired by generative adversarial networks (GANs), ELECTRA trains the model to distinguish between “real” and “fake” input data. At small scale, ELECTRA achieves strong results even when trained on a single GPU. At large scale, ELECTRA achieves state-of-the-art results on the SQuAD 2.0 dataset. Go to GitHub where you can access the three models (ELECTRA-Small, ELECTRA-Base and ELECTRA-Large). -
Google
FLAN-T5
FREEIf you already know T5, FLAN-T5 is just better at everything. For the same number of parameters, these models have been fine-tuned on more than 1,000 additional tasks covering more languages – the NLP is for English, German, French. It has Apache-2.0 license which is a permissive open source license that allows for commercial use. With appropriate prompting, it can perform zero-shot NLP tasks such as text summarization, common sense reasoning, natural language inference, question answering, sentence and sentiment classification, translation, and pronoun resolution. -
Google
Flan-UL2
FREEDeveloped by Google, Flan-UL2, which is a more powerful version of the T5 model that has been trained using Flan, and it is downloadable from Hugging Face. It shows performance exceeding the ‘prior’ versions of Flan-T5. With the ability to reason for itself and generalize better than the previous models, Flan-UL2 is a great improvement. Flan-UL2 is a machine learning model that can generate textual descriptions of images and has the potential to be used for image search, video captioning, automated content generation, and visual question answering. Flan-UL2 has an Apache-2.0 license, which is a permissive open source license that allows for commercial use.If Flan-UL2’s 20B parameters are too much, consider the previous iteration of Flan-T5, which comes in five different sizes and might be more suitable for your needs. -
EleutherAI
GPT-J
FREEEleutherAI is a leading non-profit research institute focused on large-scale artificial intelligence research. EleutherAI has trained and released several LLMs and the codebases used to train them. GPT-J can be used for code generation, making a chat bot, story writing, language translation and searching. GPT-J learns an inner representation of the English language that can be used to extract features useful for downstream tasks. The model is best at what it was pretrained for, which is generating text from a prompt. EleutherAI has a web page where you can test to see how the GPT-J works, or you can run GPT-J on google colab, or use the Hugging Face Transformers library. -
EleutherAI
GPT-NeoX-20B
FREEEleutherAI has trained and released several LLMs and the codebases used to train them. EleutherAI is a leading non-profit research institute focused on large-scale artificial intelligence research. GPT-NeoX-20B is a 20 billion parameter autoregressive language model trained on the Pile using the GPT-NeoX library. Its architecture intentionally resembles that of GPT-3, and is almost identical to that of GPT-J- 6B. Its training dataset contains a multitude of English-language texts, reflecting the general-purpose nature of this model. It is a transformer-based language model and is English-language only, and thus cannot be used for translation or generating text in other languages. It is freely and openly available to the public through a permissive license. -
AI21 Labs
Jurassic-2 Grande (Base & Instruct)
$0.01J2-Grande offers enhanced text generation capabilities, making it well-suited to language tasks with a greater degree of complexity. Its fine-tuning options allow for optimization of quality, while maintaining an affordable price and high efficiency (see site for more details). It is an ideal choice for complex language processing tasks and generative text applications. All of J2 models support several non-English languages, including: Spanish, French, German, Portuguese, Italian and Dutch. All Jurassic foundation models are trained on a massive corpus of text, making them a powerful basis for a wide range of natural language processing applications, capable of understanding and composing human-like text. Models are available through an API and you can start with a free trial and then pay based on usage. -
AI21 Labs
Jurassic-2 Jumbo (Base & Instruct)
$0.015As the largest and most powerful model in the Jurassic series, J2-Jumbo is an ideal choice for the most complex language processing tasks and generative text applications. Further, the model can be fine-tuned for optimum performance in any custom application. Jurassic-2 not only improves upon Jurassic-1 (AI21 Studio previous generation models) in every aspect, making it highly versatile in general purpose text-generators, and capable of composing human-like text and solving complex tasks such as question answering and text classification. All of the J2 models support several non-English languages, including: Spanish, French, German, Portuguese, Italian and Dutch. All Jurassic foundation models are trained on a massive corpus of text, making them a powerful basis for a wide range of natural language processing applications, capable of understanding and composing human-like text. Models are available through an API and you can start with a free trial and then pay based on usage. -
AI21 Labs
Jurassic-2 Large (Base & Instruct)
$0.003Designed for fast responses, the Jurassic-2 Large model can be fine-tuned to optimize performance for relatively simple tasks, making it an ideal choice for language processing tasks that require maximum affordability and less processing power. All of the J2 models support several non-English languages, including: Spanish, French, German, Portuguese, Italian and Dutch. All Jurassic foundation models are trained on a massive corpus of text, making them a powerful basis for a wide range of natural language processing applications, capable of understanding and composing human-like text. Models are available through an API and you can start with a free trial and then pay based on usage.
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Google
LaMDA
OTHERLaMDA stands for Language Model for Dialogue Application. It is a conversational Large Language Model (LLM) built by Google as an underlying technology to power dialogue-based applications that can generate natural-sounding human language. LaMDA is built by fine-tuning a family of Transformer-based neural language models specialized for dialog and teaching the models to leverage external knowledge sources. The potential use cases for LaMDA are diverse, ranging from customer service and chatbots to personal assistants and beyond. LaMDA is not open source; currently, there are no APIs or downloads. However, Google is working on making LaMDA more accessible to researchers and developers. In the future, it is likely that LaMDA will be released as an open source project, and that APIs and downloads will be made available. -
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.
