Deep Dive into OpenHermes 2.5: Capabilities, Performance, and Impact

Table of Contents

• Introduction
• Benchmark Results and Performance
• How to Use OpenHermes 2.5
• Comparing OpenHermes 2.5 to Lama 2 13B and GPT-4
• The Impact and Potential of OpenHermes 2.5
• Conclusion and Key Takeaways

Introduction to OpenHermes 2.5 - A Cutting Edge AI Model

The AI landscape has seen massive advances in recent years, with innovative new models being developed at a rapid pace. One of the latest buzzworthy models is OpenHermes 2.5 - an open source AI system that demonstrates extremely impressive capabilities despite its relatively small size.

In this post, we'll provide an overview of OpenHermes 2.5, discuss its key features and performance benchmarks, provide a step-by-step guide on using the model, and compare it to other leading AI systems like LLAMa-213B and GPT-4.

What is OpenHermes 2.5?

OpenHermes 2.5 Mistral 7B is a cutting edge Mistral fine-tuned model based on the Mistral 7B architecture. It has achieved further performance improvements by undergoing additional training on primarily GPT-4 generated data, as well as other high-quality datasets. Specifically, OpenHermes 2.5 was trained on 100,000 entries of GPT-4 generated text, which accounted for around 7-14% of its total training data. The remainder of its dataset came from sources like Glaive AI, a16z, and dozens of other organizations and individuals. This supplementary training on synthetic GPT-4 data has led to considerable boosts in OpenHermes 2.5's capabilities, allowing it to excel across a diverse range of AI benchmarks and tasks.

Key Features of OpenHermes 2.5

Here are some of the key capabilities and features of OpenHermes 2.5:

• State-of-the-art performance in benchmarks like BigBench, TruthfulQA, and HellaSwag
• Significantly improved abilities compared to the base Mistral 7B model
• Surpasses OpenChat 3.5 despite being a smaller model
• Strong performance in coding tasks and code generation
• Refusal to provide unethical or illegal information, demonstrating improved ethics

Benchmark Results and Performance of OpenHermes 2.5

Numerous benchmarks have been conducted to evaluate OpenHermes 2.5 against other leading AI models. The results demonstrate that it achieves state-of-the-art performance despite its relatively small size.

In BigBench, TruthfulQA, and HellaSwag evaluations, OpenHermes 2.5 attained the highest scores among all Mistral fine-tuned models. It even exceeded the performance of OpenChat 3.5, which is considered comparable to ChatGPT.

Tests focused specifically on coding also show promising results. In HumanEval coding tasks, OpenHermes 2.5 scored around 4 times higher than LLAMa-27B, indicating a significant enhancement in code generation abilities thanks to its training on GPT-4 generated code data.

How to Use OpenHermes 2.5

Using OpenHermes 2.5 is straightforward with the right tools. Here is a simple step-by-step guide to start leveraging this powerful AI model on your own computer:

Downloading and Loading the Model

First, download the LM Studio app for Windows or Mac. This allows you to run large language models entirely offline on your own device. Once installed, open LM Studio and search for 'OpenChat'. Select the OpenHermes 2.5 variant you want to use and click the download button. After the download completes, go to the Chat interface on the left sidebar. At the top, select the OpenHermes 2.5 model file to load. That's it! The model will now be loaded locally on your computer and ready for you to chat with.

Chatting with the Model

With OpenHermes 2.5 loaded, you can simply enter prompts and questions into the chat interface to leverage its advanced capabilities. Go ahead and chat about any topic - OpenHermes 2.5 can provide detailed, coherent responses on everything from casual conversation to complex technical subjects. Its performance is extremely impressive given the model's efficiency and size. Feel free to experiment with code generation prompts as well. You'll likely find that OpenHermes 2.5 can generate high-quality code similar to GPT-4.

Comparing OpenHermes 2.5 to LLAMa-213B and GPT-4

Given the hype surrounding OpenHermes 2.5, how does it stack up against other popular AI models like LLAMa-213B and GPT-4? Let's evaluate:

• In general capabilities, OpenHermes 2.5 is on par with LLAMa-213B and GPT-4, despite being much smaller in size

• For coding tasks specifically, it outperforms LLAMa-213B and is comparable to GPT-4 in code generation quality

• OpenHermes 2.5 appears to have greater ethical awareness - for example, refusing prompts that request illegal information

• With its training on GPT-4 data, OpenHermes 2.5 demonstrates abilities that cut across both conversational and technical domains

The Impact and Potential of OpenHermes 2.5

The techniques used to develop OpenHermes 2.5 could have wide-ranging impacts on AI research and development. Its performance improvements from supplementary training on GPT-4 generated data provide a template for efficiently enhancing future models.

The open source nature of OpenHermes 2.5 also unlocks exciting possibilities. As more researchers build on this model, we might see rapid open source innovation that leads to AI 'self-evolving' without reliance on private companies.

Finally, the ability to run advanced models like OpenHermes 2.5 offline on modest consumer hardware unlocks AI accessibility. The playing field is being leveled so that anyone can leverage state-of-the-art AI to empower their lives.

Conclusion and Key Takeaways on OpenHermes 2.5

OpenHermes 2.5 demonstrates extremely impressive capabilities for its size and training approach, achieving benchmarks comparable to far larger models like GPT-4.

Key takeaways:

• Cutting-edge performance on par with models 10x its size

• Efficient training with GPT-4 synthetic data

• Excellent coding abilities, outperforming LLAMa-213B

• Refusal to provide unethical information shows improved ethics

• Huge potential impact as an open source model

FAQ

Q: What is OpenHermes 2.5?
A: OpenHermes 2.5 is a state-of-the-art fine-tuned version of Anthropic's Mistral 7B model. It was trained on 100,000 entries of GPT-4 generated data.

Q: How does OpenHermes 2.5 perform compared to other LLMs?
A: Benchmark results show OpenHermes 2.5 outperforming other Mistral fine-tuned models. It also exceeds OpenChat 3.5 and has 4x higher coding ability than Lama 27B.

Q: What can OpenHermes 2.5 be used for?
A: OpenHermes 2.5 can be used for a variety of natural language tasks. Its strong coding ability also makes it suitable for generating code.

Q: How was OpenHermes 2.5 trained?
A: OpenHermes 2.5 was trained on 1,00,000 entries of primarily GPT-4 generated data as well as high-quality datasets.

Q: Does OpenHermes 2.5 have ethical safeguards?
A: Yes, additional learning has helped improve OpenHermes 2.5's ethics. It refuses to provide illegal information unlike its base Mistral 7B model.

Q: What is the potential impact of OpenHermes 2.5?
A: The knowledge gained from building OpenHermes 2.5 could significantly streamline LLM development, potentially enabling AI self-evolution.

Q: How can I use OpenHermes 2.5?
A: You can download OpenHermes 2.5 through Anthropic's LM Studio and chat with the model through the app's interface or a local server.

Q: Where can I learn more about OpenHermes 2.5?
A: Check the links in the video description for more details and resources on OpenHermes 2.5 capabilities and performance.

Q: Is OpenHermes 2.5 better than GPT-4?
A: While comparable in many areas, OpenHermes 2.5 does not exceed GPT-4 overall. However, it matches GPT-4's coding ability despite being much smaller.

Q: Can I run OpenHermes 2.5 locally?
A: Yes, with Anthropic's LM Studio you can run OpenHermes 2.5 entirely offline on your own laptop.