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OneLLM Fine-tune, evaluate, and deploy your next LLM without code.

What is OneLLM?

OneLLM provides a comprehensive, no-code solution for developing and deploying Large Language Models (LLMs). The platform allows users to manage the entire LLM lifecycle, starting from dataset creation directly within the browser interface. Users can input chat interactions between a user and an assistant to build the necessary training data without external tools.

Once a dataset is prepared, users integrate their OpenAI API key to access the fine-tuning capabilities (with planned support for other models like Gemini and Llama). The fine-tuning process involves selecting a base model and configuring hyperparameters according to specific needs. After training, OneLLM offers tools to evaluate the model's performance, including testing, scoring, and visualizing improvements through an auto-generated heatmap comparing the fine-tuned model against base models. Finally, the platform facilitates deployment through its SDK or by simple configuration changes for existing OpenAI library users, along with features to record and monitor model usage and performance.

Features

  • No-code Interface: Fine-tune, evaluate, and deploy LLMs without writing any code.
  • In-browser Dataset Creation: Build custom chat datasets directly within the platform.
  • API Key Integration: Connect your OpenAI API key (support for Gemini, Llama planned).
  • Customizable Fine-tuning: Choose base models and set hyperparameters for training.
  • Performance Evaluation Tools: Test models, assign scores, and view comparison heatmaps.
  • Simplified Deployment: Deploy models using the OneLLM SDK or minimal configuration changes.
  • Usage & Performance Tracking: Monitor deployed model usage and effectiveness.

Use Cases

  • Improving LLM response structure for specific tasks (e.g., code generation).
  • Enhancing chatbot performance for better customer service.
  • Streamlining LLM integration into products for diverse teams.
  • Facilitating experimentation with different LLM datasets and fine-tuning strategies.
  • Reducing the time and technical resources required for LLM development.

FAQs

  • How do I make a dataset on OneLLM?
    You can create a dataset directly within the OneLLM browser interface by writing the chat interactions between a user and an assistant.
  • Do I need coding skills to use OneLLM?
    No, OneLLM is designed as a no-code platform, allowing you to fine-tune, evaluate, and deploy Large Language Models without writing any code.
  • How can I assess if my fine-tuned model has improved?
    After training, you can test the model, assign it a score, and view an automatically generated heatmap that compares its performance against the base models.

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