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  • Google, Stanford University

    Electra

    FREE
    ELECTRA (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).

  • Technology Innovation Institute

    Falcon-40B

    OTHER
    The Technology Innovation Institute (TII), an Abu Dhabi government funded research institution, has introduced Falcon, a state-of-the-art autoregressive decoder-only language model series released under the Apache 2.0 license, which means it can be used for commerical and research uses.
    The family includes Falcon-40B and Falcon-7B, trained on 1 trillion tokens, mainly (>80%) from the RefinedWeb datase. A special variant, Falcon-40B-Instruct, has been made available which may be more suitable for assistant-style tasks. Falcon-40B can support English, German, Spanish, French (and limited capabilities in Italian, Portuguese, Polish, Dutch, Romanian, Czech, Swedish). It can be used to generate creative text and solve complex problems, chatbots, virtual assistants, language translation, content generation, and sentiment analysis (and more).

    To use these models, PyTorch 2.0 is required. TII is now calling for proposals from users worldwide to submit their most creative ideas for Falcon 40B’s deployment – https://falconllm.tii.ae/call-for-proposal.php or you can pay to access it via Amazon SageMaker JumpStart.
    A demo of Falcon-Chat is available on Hugging Face at https://huggingface.co/spaces/HuggingFaceH4/falcon-chat.

  • Technology Innovation Institute

    Falcon-7B

    FREE

    The Technology Innovation Institute (TII), an Abu Dhabi government funded research institution, has introduced Falcon, a state-of-the-art autoregressive decoder-only language model series released under the Apache 2.0 license, which means it can be used for commerical and research uses. Falcon-7B only needs ~15GB and therefore is accessible even on consumer hardware. The model can support English, German, Spanish, French (and limited capabilities in Italian, Portuguese, Polish, Dutch, Romanian, Czech, Swedish). It can be used to generate creative text and solve complex problems, chatbots, customer service operations, virtual assistants, language translation, content generation, and sentiment analysis.

    This raw pretrained model should be finetuned for specific use cases. Falcon-7B-Instruct is also available at https://huggingface.co/tiiuae/falcon-7b-instruct.
    If you are looking for a version better-suited model to take generic instructions in a chat format, we recommend Falcon-7B-Instruct rather than the base model.

  • Google

    FLAN-T5

    FREE
    If 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

    FREE
    Developed 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.
  • AI21 Labs

    Jurassic-2 Grande (Base & Instruct)

    $0.01
    J2-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)

    $0.015
    As 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)

    $0.003

    Designed 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.

  • Google

    LaMDA

    OTHER
    LaMDA 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.
  • Microsoft, NVIDIA

    MT-NLG

    OTHER
    MT-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.
  • Google

    PaLM 2 chat-bison-001

    $0.0021535
    PaLM 2 has just launched (May 2023) and is Google’s next-generation Large Language Model, built on Google’s Pathways AI architecture. PaLM 2 was trained on a massive dataset of text and code, and it can handle many different tasks and learn new ones quickly. It is seen as a direct competitor to OpenAI’s GPT-4 model. It excels at advanced reasoning tasks, including code and math, classification and question answering, translation and multilingual proficiency (100 languages), and natural language generation better than our previous state-of-the-art LLMs, including its predecessor PaLM.
    PaLM 2 is the underlying model driving the PaLM API that can be accessed through Google’s Generative AI Studio. PaLM 2 has four submodels with different sizes. Bison is the best value in terms of capability and chat-bison-001 has been fine-tuned for multi-turn conversation use cases. If you want to see PaLM 2 capabilities, the simplest way to use it is through Google Bard (PaLM 2 is the technology that powers Google Bard).

     

    Watch Paige Bailey introducing PaLM 2: view here

  • ChatGLM

    PaLM 2 text-bison-001

    $0.004
    PaLM 2 has just launched (May 2023) and is Google’s next-generation Large Language Model, built on Google’s Pathways AI architecture. PaLM 2 was trained on a massive dataset of text and code, and it can handle many different tasks and learn new ones quickly. It is seen as a direct competitor to OpenAI’s GPT-4 model. It excels at advanced reasoning tasks, including code and math, classification, question answering, translation and multilingual proficiency (100 languages), and natural language generation better than our previous state-of-the-art LLMs, including its predecessor PaLM.

     

    PaLM 2 is the underlying model driving the PaLM API that can be accessed through Google’s Generative AI Studio. PaLM 2 has four submodels with different sizes. Bison is the best value in terms of capability and cost, and text-bison-001 can be fine-tuned to follow natural language instructions and is suitable for various language tasks such as classification, sentiment analysis, entity extraction, extractive question answering, summarization, re-writing text in a different style, and concept ideation.

     

    If you want to see PaLM 2 capabilities, the simplest way to use it is through Google Bard (PaLM 2 is the technology that powers Google Bard).

     

    Watch Paige Bailey introducing PaLM 2: view here

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