LLaMA 2

Top Open-Source Large Language Models For 2024

The basic models of widely used and well-known chatbots, such as Google Bard and ChatGPT, are LLM. In particular, Google Bard is built on Google’s PaLM 2 model, whereas ChatGPT is driven by GPT-4, an LLM created and owned by OpenAI. The proprietary underlying LLM of ChatGPT, Bard, and numerous other well-known chatbots are shared by them. This indicates that they belong to a business and that clients can only use them with a license that they have purchased. Along with rights, that license may also impose limitations on how the LLM is used and provide access to certain technical details....

1. LLaMA 2

Most top LLM firms developed their programs discreetly. Meta stands out. Meta provided crucial information about LLaMA 2 and its powerful, open-source alternative. LLaMA 2, a 7–70 billion-parameter generative text model, finished in July 2023. This model is for business and study. The RLHF improved it. Construct and train this text generation model to teach the chatbot natural language. Meta provides open, customizable LLaMA 2, Chat, and Code Llama....

2. BLOOM

In 2022, Flourish developed BLOOM, an autoregressive Large Language Model (LLM) that generates text by extending a prompt using large amounts of textual data. Over 70 countries’ experts and volunteers developed the project in one year. The open-source LLM BLOOM model includes 176 billion parameters. It writes fluently and cohesively in 46 languages and 13 programming languages. BLOOM execution, evaluation, and improvement with training data and source code are public. Hugging Face users use BLOOM free....

3. BERT (Bidirectional Encoder Representations from Transformers)

LLM technology relies on BERT (Bidirectional Encoder Representations from Transformers) neural architecture. Google researchers released “Attention is All You Need.” in 2017. BERT was an early transformer test. The 2018 Google Language Model BERT is available as open-source software. It swiftly mastered natural language processing tasks....

4. Falcon 180B

The new Falcon 180B indicates that the difference between proprietary and open-source large language models is fast narrowing if the Falcon 40B, which ranked #1 on Hugging Face’s scoreboard for big language models, wasn’t already impressive to the open-source LLM community. Falcon 180B, which was made available by the Technology Innovation Institute of the United Arab Emirates in September 2023, is being trained using 3.5 trillion tokens and 180 billion parameters. Hugging Face indicates that Falcon 180B can compete with Google’s PaLM 2, the LLM that runs Google Bard, given its amazing processing capacity. Falcon 180B has already surpassed LLaMA 2 and GPT-3.5 in some NLP tasks....

5. OPT-175B

In 2022, Meta achieved a significant milestone with the publication of the Open Pre-trained Transformers Language Models (TLM), which was part of their aim to use open source to free the LLM race. OPT consists of a set of pre-trained transformers, decoder-only, with parameters ranging from 125M to 175B. The most potent brother is OPT-175B, an open-source LLM that is among the most sophisticated on the market and performs similarly to GPT-3. The public can access both the source code and the pre-trained models. But, you’d best think of another option if you’re planning to build an AI-driven business with LLMs, as OPT-175B is only available under a non-commercial license that permits the model’s use for research use cases....

6. XGen-7B

Businesses are entering the LLM race at an increasing rate. Salesforce was among the latest to enter the market, with the release of its XGen-7B LLM in July 2023. The authors claim that the majority of open-source LLMs concentrate on offering lengthy responses with scant details (i.e., brief prompts with little context). XGen-7B is an attempt to create a tool that can handle larger context windows. Specifically, the most sophisticated variation of XGen (XGen-7B-8K-base) supports an 8K context window—that is, the whole amount of text in both the input and output....

7. GPT-NeoX and GPT-NeoX

Generated by scientists at the nonprofit AI research center EleutherAI, GPT-NeoX and GPT-J are two excellent open-source substitutes for GPT. There are 20 billion parameters in GPT-NeoX and 6 billion in GPT-J. These two LLMs are able to produce findings with a high degree of accuracy, even though the majority of advanced LLMs can be trained using more than 100 billion parameters. They can be used in many different domains and application situations because they were trained on 22 high-quality datasets from a variety of sources. GPT-NeoX and GPT-J, in contrast to GPT-3, have not been trained using RLHF....

8. Vicuna 13-B

Using user-shared conversations collected from ShareGPT, the LLaMa 13B model was refined to create the open-source conversational model Vicuna-13B. Vicuna-13B is an intelligent chatbot with a plethora of uses; a few are shown below in various industries, including customer service, healthcare, education, finance, and travel/hospitality. According to an initial assessment using GPT-4 as a judge, Vicuna-13B surpassed other models such as LLaMa and Alpaca in more than 90% of cases, attaining over 90% quality of ChatGPT and Google Bard....

9. YI 34B

YI 34B China’s 01 AI developed a new language model called Yi 34B. Right now, this model holds the top spot on the Hugging Face Open LLM leaderboard. The company’s goal is to develop bilingual models that are capable of speaking Chinese and English. The model may now be trained on up to 32K tokens, compared to its original 4K token context window....

10. Mixtral 8x7B

Mixtral 8x7B, unveiled by Mistral AI in December 2023, is a decoder-only sparse mixture-of-experts network licensed under Apache 2.0. It outperforms LLaMA 2 and GPT 3.5 on various benchmarks despite having a smaller parameter size. With only 12.9 billion parameters per token out of a total of 46.7 billion, Mixtral achieves comparable processing rates to a 12.9B model....

Comparison of Popular LLM Models

Here’s a Comparison of Popular LLM Models:...

How to Choose right Open-Source LLM ?

Choosing the right open-source Large Language Model (LLM) involves considering several factors to ensure that it aligns with your specific needs and requirements. Here’s a guide on how to choose the right open-source LLM:...

Conclusion

The movement of open-source LLMs is quite interesting. Given their quick development, it appears that large companies with the resources to create and employ these potent instruments won’t always control the generative AI market....