🦊 How to deploy Fox-1 on TensorOpera AI: A Step-by-Step Guide

🦊 How to deploy Fox-1 on TensorOpera AI: A Step-by-Step Guide
How to deploy Fox-1 on TensorOpera AI

Welcome to our deployment guide for the Fox-1 model, now available for public use on the TensorOpera AI platform!

Getting Started

The Fox-1 model, developed by our in-house research team, can be accessed via our Model Hub. Simply click on the Fox-1 Instruct model to open the Playground, where you can test the model's responses to any prompt within seconds.

Integration Options

You can integrate the public endpoint into your application by accessing the API tab on the top left. This allows you to use the OpenAI chat-completions format for seamless integration.

For those needing a dedicated endpoint, you can deploy the model directly from your account. Just name the endpoint, select a resource type (dedicated or serverless), and choose the number of GPUs to support the model. Enabling the auto-scaling feature ensures the endpoint scales automatically based on user demand, up to a maximum of 10 replicas.

Monitoring and Management

Once deployed, you'll have access to several features:

  • Playground: Test the model with various prompts.
  • API Integration: Use the OpenAI chat-completions format.
  • System Monitoring: Track real-time traffic, model responses, latency, CPU utilization, and more.
  • Prediction Logs: Review user prompts and model outputs.
  • Deployment Logs: Debug any issues.
  • User Statistics: Monitor usage patterns.

With just a few clicks and no coding required, deploying and managing the Fox-1 model on TensorOpera AI is straightforward and efficient.

We’re excited to see how you integrate Fox-1 into your applications!