Compare Models
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ChatGLM
ChatGLM-6B
FREEResearchers at the Tsinghua University in China have worked on developing the ChatGLM series of models that have comparable performance to other models such as GPT-3 and BLOOM. ChatGLM-6B is an open bilingual language model (trained on Chinese and English). It is based on General Language Model (GLM) framework, with 6.2B parameters. With the quantization technique, users can deploy locally on consumer-grade graphics cards (only 6GB of GPU memory is required at the INT4 quantization level). The following models are available: ChatGLM-130B (an open source LLM), ChatGLM-100B (not open source but available through invite-only access), and ChatGLM-6 (a lightweight open source alternative). ChatGLM LLMs are available with a Apache-2.0 license that allows commercial use. We have included the link to the Hugging Face page where you can try the ChatGLM-6B Chatbot for free. -
OpenAI
ChatGPT (Web Browser Version)
FREEThe ChatGPT Web Browser Version is an accessible online powerful language model. The chatbot is designed to provide users with a user-friendly interface that facilitates interaction without needing any specialized programming or machine learning knowledge. Users can leverage ChatGPT for a wide range of applications, including but not limited to tutoring in academic subjects, generating creative content, drafting and editing text, providing personalized recommendations, translating languages, and even programming help. Businesses can use it for automating customer service, generating marketing content, and providing personalized user experiences.ChatGPT is powered by GPT-3.5-turbo by default and is free to try. If you are a paying customer and subscribe to ChatGPT Plus, you can change the model to GPT-4 before you start a chat. Currently, the ChatGPT models support several languages, including but not limited to English, Spanish, French, German, Portuguese, Italian and Dutch. New features for ChatGPT-Plus users have just been announced. These include a web-browsing feature that provides up-to-date information (prior to the update, ChatGPT was limited in what it could answer, as it was only trained on data until 2021). ChatGPT-Plus users can also access third-party plug-ins for web services like Expedia, Kayak, and Instacart. With these plug-ins, users can prompt ChatGPT to perform tasks on specific websites. -
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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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. -
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. -
Meta AI
Llama
FREEMeta has created Llama (Large Language Model Meta AI), its state-of-the-art foundational large language model designed to help researchers advance their work in this subfield of AI. Smaller, more performant models such as LLaMA enable others in the research community who don’t have access to large amounts of infrastructure to study these models, further democratizing access in this important, fast-changing field.Training smaller foundation models like Llama is desirable in the Large Language Model space because it requires far less computing power and resources to test new approaches, validate others’ work, and explore new use cases. Foundation models train on a large set of unlabeled data, which makes them ideal for fine-tuning for a variety of tasks. Meta is making Llama available at several sizes (7B, 13B, 33B, and 65B parameters) and they also share a Llama model card that details how we built the model in keeping with our approach to responsible AI practices. -
Meta AI
Llama 2
FREEMeta has released Llama 2. It has an open license, which allows commercial use for businesses. Llama 2 will be available for use in the Hugging Face Transformers library from today (you will need to sign Meta’s Llama 2 Community License Agreement – https://ai.meta.com/resources/models-and-libraries/llama-downloads/, via MSFT Azure cloud computing service, and through Amazon SageMaker JumpStart).Llama 2 is an auto-regressive language model that uses an optimized transformer architecture. Llama 2 is intended for commercial and research use in English. It comes in a range of parameter sizes—7 billion, 13 billion, and 70 billion—as well as pre-trained and fine-tuned variations. According to Meta, the tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align to human preferences for helpfulness and safety. Llama 2 was pre-trained on 2 trillion tokens of data from publicly available sources. The tuned models are intended for assistant-like chat, whereas pre-trained models can be adapted for a variety of natural language generation tasks.Link to the live demo of Llama2 70B Chatbot -https://huggingface.co/spaces/ysharma/Explore_llamav2_with_TGI -
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.
