OpenChat 3.5: The Open-Source LLM Outperforming Industry Giants

Name

Jennie Rose

Published on 4/30/2024

OpenChat 3.5 is a groundbreaking open-source language model developed by the OpenChat team. With just 7 billion parameters, it achieves remarkable performance that rivals or surpasses industry-leading models like ChatGPT and Grok. What sets OpenChat 3.5 apart is its commitment to open-source accessibility, enabling developers and researchers to leverage its capabilities without the constraints of proprietary licenses.

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Key Features of OpenChat 3.5

• Efficient Training with C-RLFT: OpenChat 3.5 is trained using Conditioned Reinforcement Learning from Feedback (C-RLFT), a technique inspired by offline reinforcement learning. This approach allows the model to learn effectively from mixed-quality data without explicit preference labels.

• Exceptional Performance with Fewer Parameters: Despite having only 7 billion parameters, OpenChat 3.5 delivers performance comparable to or better than models with significantly more parameters, such as ChatGPT and Grok.

• Accessible Deployment: OpenChat 3.5 can be run on consumer-grade GPUs like the RTX 3090, making it more accessible to developers and researchers compared to resource-intensive proprietary models.

• Versatile Capabilities: OpenChat 3.5 excels as a generalist model, demonstrating strong performance across a wide range of tasks, including coding, question-answering, and language understanding.

Benchmark Results

OpenChat 3.5 has demonstrated impressive results across various benchmarks, solidifying its position as a top-performing open-source language model. Here are some notable benchmark comparisons:

As evident from the table, OpenChat 3.5 outperforms Grok-0 (33B parameters) on all four benchmarks and surpasses Grok-1 (unknown parameters) on average and in 3 out of 4 benchmarks. It also achieves results comparable to or better than ChatGPT (March 2023 version) in key areas like HumanEval and GSM8k, despite having significantly fewer parameters.

Running OpenChat 3.5 Locally with Ollama

One of the key advantages of OpenChat 3.5 is the ability to run it locally using tools like Ollama. Here's a step-by-step guide:

1. Install Ollama by running the following command:

   curl -fsSL https://ollama.com/install.sh | sh

2. Download the OpenChat 3.5 model using the Ollama command:

   ollama run openchat

3. Start the Ollama server:

   ./ollama serve

4. In a separate shell, run the OpenChat 3.5 model:

   ./ollama run openchat

5. Interact with the model using the Ollama REST API or one of the compatible user interfaces, such as:

   • LibreChat
   • Bionic GPT
   • Enchanted (macOS native)
   • HTML UI
   • Saddle
   • Chatbot UI

Here's an example of how to generate text using the Ollama REST API:

curl http://localhost:11434/api/generate -d '{
  "model": "openchat",
  "prompt": "Why is the sky blue?"
}'

And here's how to engage in a chat-like interaction:

curl http://localhost:11434/api/chat -d '{
  "model": "openchat",
  "messages": [
    {
      "role": "user",
      "content": "Why is the sky blue?"
    }
  ]
}'

By following these steps, you can easily run OpenChat 3.5 locally and experience its impressive capabilities firsthand.

Potential Applications and Impact

OpenChat 3.5 has the potential to revolutionize the AI landscape by providing a highly capable open-source language model that is accessible to developers and researchers worldwide. Some potential applications include:

• Coding Assistance: With its strong performance on coding benchmarks like HumanEval, OpenChat 3.5 can serve as a powerful coding assistant, helping developers write more efficient and error-free code.

• Question Answering: OpenChat 3.5's exceptional performance on benchmarks like MMLU and GSM8k demonstrates its ability to provide accurate and informative answers to a wide range of questions.

• Language Understanding: The model's strong performance on language understanding tasks makes it suitable for applications like sentiment analysis, text classification, and named entity recognition.

• Research and Innovation: By providing an open-source alternative to proprietary models, OpenChat 3.5 enables researchers to explore new ideas and push the boundaries of what's possible with language models.

Conclusion

OpenChat 3.5 represents a significant milestone in the development of open-source language models. With its exceptional performance, efficient resource usage, and accessibility, it has the potential to democratize access to powerful AI tools and accelerate research and innovation in the field.

As the AI landscape continues to evolve, models like OpenChat 3.5 will play a crucial role in shaping the future of natural language processing and AI-driven applications. By embracing open-source initiatives and collaborating with the global AI community, we can unlock new possibilities and drive the development of even more advanced and capable language models.

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