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UF Navigator AI
NaviGator AI allows you to use different Large Language Models (LLMs) with your own dataset. You can use AI to discover trends and patterns, look for insights, and produce reports based on your data. Available to UF Students, Faculty, and Staff.
During this pilot, the cost is covered by UF President's block grant. There is no charge for using the service.
Security, Privacy, Data Classification Usage Guidelines
UF provides this service to allow you to analyze your documents using different language models while keeping those documents secure within UF servers and contracted vendors. At this time, UF does not permit the usage of restricted or sensitive data with this service. Users only have access to their own datasets and conversation history. When interacting with the language models hosted by vendors, your messages and subsets of your documents will be sent to a LLM instance provided by Microsoft or Google. All data handled in this fashion is covered by our existing agreements with Microsoft and Google. None of this data contributes to training the large language model. No data is retained after deletion. If you have uploaded a file by accident, deleting the file or conversation will completely remove it from the system.
*During this pilot accessing Navigator AI off-campus requires UF Gatorlink VPN Service.
Using UF NaviGator AI
Available Language Models
|
Models |
Hosting |
|
llama3-8b-instruct |
UF HiPerGator |
|
llama3-70b-instruct |
UF HiPerGator |
|
mistral-7b-instruct |
UF HiPerGator |
|
mistral-8x7b-instruct |
UF HiPerGator |
|
mistral-large |
UF HiPerGator |
|
Codestral-22b |
UF HiPerGator |
|
gemma-1.1-7b-it |
UF HiPerGator |
|
gpt-3.5-turbo |
Microsoft Azure |
|
gpt-4-turbo |
Microsoft Azure |
|
gpt-4o |
Microsoft Azure |
|
gemini-1.5-pro |
|
|
gemini-1.0-pro |
|
|
gemini-1.5-flash |
|
|
claude-3-haiku |
Amazon Web Services |
|
Claude-3-sonnet |
Amazon Web Services |
|
Claude-3.5-sonnet |
Amazon Web Services |
|
Claude-3-opus |
Amazon Web Services |
|
Command-r |
Amazon Web Services |
|
Command-r-plus |
Amazon Web Services |
Language model preset parameters
|
Parameter |
Description |
|
Model |
Select the model like gpt-3.5-turbo that will be used for generating responses |
|
Custom Name |
Optionally provide a custom name for your preset. This is the name that will be shown in the UI when using it |
|
Custom Instructions |
Define instructions or guidelines that will be displayed before each prompt to guide the user in providing input |
|
Temperature |
Adjust this parameter to control the randomness of the model’s output. A higher value makes the output more random, while a lower value makes it more focused and deterministic |
|
Top P |
Control the nucleus sampling parameter to influence the diversity of generated text. Lower values make text more focused while higher values increase diversity |
|
Frequency Penalty |
Use this setting to penalize frequently occurring tokens and promote diversity in responses |
|
Presence Penalty |
Adjust this parameter to penalize new tokens that are introduced into responses, controlling repetition and promoting consistency |