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Secure, unlimited storage to ensures efficiency as well as high and continuous data access demand.
Virtual server integration for 3D Rendering, AI or ML
Enhance application capacity and availability.
Access to an all-inclusive stack for AI development, driven by NVIDIA’s powerful technology!
FPT Web Application Firewall provides powerful protection for web applications
Advanced virtual server with rapid scalability
Backup and restore data instantly, securely and maintain data integrity.
Advanced virtual server with rapid scalability
Access to an all-inclusive stack for AI development, driven by NVIDIA’s powerful technology!
Enhance application capacity and availability.
Backup and restore data instantly, securely and maintain data integrity.
Recovery, ensuring quick operation for the business after all incidents and disasters.
Diverse throughput and capacity to meet various business workloads.
Secure, unlimited storage to ensures efficiency as well as high and continuous data access demand.
FPT Web Application Firewall provides powerful protection for web applications
Intelligent and Comprehensive Virtual Web Application Firewall - Security Collaboration between FPT Cloud and Penta Security.
The Next generation firewall security service
Easily store, manage, deploy, and secure Container images
Safe, secure, stable, high-performance Kubernetes platform
Provided as a service to deploy, monitor, backup, restore, and scale MongoDB databases on cloud.
Provided as a service to deploy, monitor, backup, restore, and scale Redis databases on cloud.
Provided as a service to deploy, monitor, backup, restore, and scale PostgreSQL databases on cloud.
System Monitoring Solution anywhere, anytime, anyplatform
Helps reduce operational costs by up to 40% compared to traditional BI solutions, while improving efficiency through optimized resource usage and infrastructure scaling. - Pricing
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AI Inference
Deployment (LoRA Inference)
Deployment (LoRA Inference)
How to deploy a fine-tuned LoRA model?
User story:
As a user, I want to deploy my fine-tuned LoRA model so that I can use it immediately via API without managing infrastructure.
Steps
- Go to the Deployment page from the navigation bar.
- Or click View deployment from the success pop-up after fine-tuning.
- Click Deploy next to the LoRA model you want to deploy.
- Status will change to Deploying.
- Once deployment is successful, the status will show Deployed.
How to manage deployed models?
On the Deployment page, you can:
- Get API Key – Retrieve the key to call your model.
- View API request – Open a pop-up with sample JSON response.
- Try in Playground – Test the model directly in the UI.
- Undeploy – Stop the deployed model (confirmation required).
Status badges
- Deploying – Model is being deployed.
- Deployed – Model is ready for inference.
- Stopped – Model is undeployed.
- Failed – Deployment failed.
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