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. -
Databricks
Dolly 2.0
FREEDolly 2.0 by Databricks, is the first open source, instruction-following Large Language Model, fine-tuned on a human-generated instruction dataset and is licensed for research and commercial use, which means any organization can create, own, and customize powerful LLMs that can talk to people without paying for API access or sharing data with third parties.Dolly 2.0 is a 12B parameter language model based on the EleutherAI pythia model family and fine-tuned exclusively on a new, high-quality human generated instruction following dataset (crowdsourced among Databricks employees – so cool). Dolly-v2-12b is not a state-of-the-art model, but it does exhibit surprisingly high-quality instruction following behavior not characteristic of the foundation model on which it is based. Dolly v2 is also available in smaller model sizes: dolly-v2-7b, a 6.9 billion parameter based on pythia-6.9b and dolly-v2-3b, a 2.8 billion parameter based on pythia-2.8b.Dolly 2.0 can be used for brainstorming, classification, open Q&A, closed Q&A, content generation, information extraction, and summarization. You can access the Dolly 2.0 can training code, the dataset, and the model weights on Hugging Face. -
Technology Innovation Institute
Falcon-40B
OTHERThe 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
FREEThe 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. -
Cohere
Generate
$0.015Cohere is a Canadian startup that provides high-performance and secure LLMs for the enterprise. Their models work on public, private, or hybrid clouds.Cohere Generate can be used for tasks such as copywriting, named entity recognition, paraphrasing, and summarization. It can be particularly useful for automating time-consuming and repetitive copywriting tasks and re-wording text to suit a specific reader or context.Cohere Generate is available as an API that can be integrated into various libraries using Python, Node, or Go software development kits (SDKs).We have shown the price of the Cohere Generate Default version, but a Cohere Generate Custom model is available but is double the price (0.030 per 1/k tokens). However, custom models can lead to some of the best-performing NLP models for many tasks. -
Amazon
SageMaker
FREEAmazon SageMaker enables developers to create, train, and deploy machine-learning (ML) models in the cloud. SageMaker also enables developers to deploy ML models on embedded systems and edge-devices. Amazon SageMaker JumpStart helps you quickly and easily get started with machine learning. The solutions are fully customizable and supports one-click deployment and fine-tuning of more than 150 popular open source models such as natural language processing, object detection, and image classification models that can help with extracting and analyzing data, fraud detection, churn prediction and personalized recommendations.The Hugging Face LLM Inference DLCs on Amazon SageMaker, allows support the following models: BLOOM / BLOOMZ, MT0-XXL, Galactica, SantaCoder, GPT-Neox 20B (joi, pythia, lotus, rosey, chip, RedPajama, open assistant, FLAN-T5-XXL (T5-11B), Llama (vicuna, alpaca, koala), Starcoder / SantaCoder, and Falcon 7B / Falcon 40B. Hugging Face’s LLM DLC is a new purpose-built Inference Container to easily deploy LLMs in a secure and managed environment. -
Cohere
Summarize
$0.015Cohere is a Canadian startup that provides high-performance and secure LLMs for the enterprise. Their models work on public, private, or hybrid clouds and is available as an API that can be integrated into various libraries using Python, Node, or Go software development kits (SDKs).Cohere Summarize generates a succinct version of a provided text. This summary relays the most important messages of the text, and a user can configure the results with a variety of parameters to support unique use cases. It can instantly encapsulate the key points of a document and provides text summarization capabilities at scale.
