What is fine-tuning?
Fine-tuning is the process of further training a pre-trained AI model on your organization's specific data to customize its behavior, knowledge, and outputs. It adjusts the model's weights to perform better on your particular use cases.
Fine-Tuning Process
How fine-tuning works
Every feature designed to help your team work smarter with AI.
Training data preparation
Curate high-quality examples of the inputs and outputs you want the model to produce for your specific use cases.
Model training
Train the base model on your dataset, adjusting its weights to align with your desired behavior and output style.
Evaluation and testing
Assess the fine-tuned model against benchmarks to ensure it performs better than the base model on your tasks.
Iterative refinement
Improve results through multiple rounds of data curation, training, and evaluation until performance meets your standards.
Data security
Ensure training data is handled securely and that sensitive information does not leak through the fine-tuned model's outputs.
Prompt optimization
Even fine-tuned models benefit from well-engineered prompts. Optimize prompts for your custom model to maximize performance.
Benefits
When fine-tuning makes sense
FAQ
Frequently asked questions
Should I fine-tune or use better prompts?
Start with prompt engineering — it is faster, cheaper, and more flexible. Fine-tune only when prompt optimization has been exhausted and you need capabilities that prompting alone cannot provide. TeamPrompt helps you optimize prompts first.
How does TeamPrompt relate to fine-tuning?
TeamPrompt helps teams optimize prompts before and after fine-tuning. Good prompt engineering often eliminates the need for fine-tuning. When fine-tuning is necessary, TeamPrompt helps manage the prompts used with custom models.
Is fine-tuning expensive?
Fine-tuning costs vary by provider and model size, but it requires both compute costs and significant human effort for data preparation. Prompt engineering through TeamPrompt is typically much more cost-effective.
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Learn moreHow it works
Three steps from install to full AI security coverage.
Install
Add the browser extension to Chrome, Edge, or Firefox — or deploy it to your whole team via MDM. No proxy or VPN needed.
Configure
Enable the compliance packs for your industry, set DLP rules, and add your team's prompts to the shared library.
Protected
Every AI interaction is scanned in real time. Sensitive data is blocked before it leaves the browser. Your team has a full audit trail.
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