GPT Fine Tuning as a Service: Build Your Own Custom AI

We're excited to announce our new service: GPT fine tuning as a service.

10 months ago   •   2 min read

By Peter Foy

Looking to create a fine tuned GPT-3.5 model for your specific use case? We offer expert fine-tuning services to build and optimize your LLM-enabled applications.

If you're looking to achieve better results, reduce latency, and save costs on a wide range of natural language processing (NLP) tasks, we're here to help.

GPT 3.5 Fine Tuning Use Cases

  • Brand Tone of Voice: Craft customer interactions that align with your brand's identity.
  • Reliable Output Formatting: Standardize text outputs, for example for named entity extraction, summarization, and so on.
  • Cost Optimization: Minimize token usage by providing training examples instead of prompt stuffing to cut costs.

Fine Tuning Industry Applications

Below are are few industry applications of fine tuning.

  • Customer Service & Documentation: Automate common questions and direct users to relevant documentation by training on customer interactions.
  • Marketing and Advertising: Enhance ad copy and target audience identification by fine-tuning in your brand tone of voice.
  • News & Journalism: Enhance automated story generation and fact-checking by training on verified news articles.
  • E-commerce: Improve product recommendation and customer reviews by fine-tuning on transaction and user interaction data.
  • Education & E-learning: Personalize learning experiences by training the model on educational material tailored to individual needs.
  • Software Development: Assist with debugging and generate code snippets by training on software repositories.

GPT 3.5 fine tuning Tutorials

For those interested learning fine tuning themselves, we've written multiple tutorials on how to fine-tune GPT-3.5 models:

How It Works:

  1. Submit your use case: Let us know your fine tuning or custom knowledge needs—brand tone, output formatting, etc.
  2. Initial consultation: Answer a few questions to help us understand your desired training dataset.
  3. Sample dataset & approval: We create a sample dataset for your approval.
  4. Fine tuning: We then fine-tune the GPT-3.5 model to meet your requirements.
  5. Demo bot deployment: We then deploy the model in a private or public Streamlit app so you can interact with it. We also have options to deploy the chatbot on any website and integrate it into third party apps like Whatsapp, Messenger, & more.

Sample: Fine tuning Q&A chatbot

Below is an example of a custom knowledge bot with information on GPT fine tuning, embeddings, and more. You can ask questions like...

what's the difference between fine tuning and embeddings?

Who is this for?

From startups, scaleups, to larger organizations, we provide customized solutions tailored for your unique needs.

Contact us below to learn more about pricing.

GPT Fine Tuning Request

If you have any questions about GPT fine tuning, you can just submit the form and we'll be happy to discuss your use case.

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