Tensorfuse

What is Tensorfuse?

Tensorfuse is a cutting-edge platform that simplifies running generative AI models by managing Kubernetes clusters on your own cloud infrastructure. It enables serverless GPU usage with autoscaling capabilities that scale resources to zero when idle and rapidly scale up to meet demand. Tensorfuse supports diverse hardware including GPUs (A10G, A100, H100), TPUs, Trainium/Inferentia chips, and FPGAs, allowing flexible and efficient model deployment. The platform offers OpenAI-compatible APIs, serverless training jobs, and built-in finetuning methods like LoRA and QLoRA, all abstracting away complex infrastructure management to accelerate AI development and reduce cloud GPU costs.

Key Features

• Serverless GPU Management

  Automatically scales GPU resources from zero to handle concurrent workloads without manual intervention.

• Multi-Hardware Support

  Runs AI workloads on various hardware including NVIDIA GPUs, TPUs, Trainium/Inferentia chips, and FPGAs.

• OpenAI-Compatible API

  Expose your AI models through APIs compatible with OpenAI standards for easy integration.

• Built-in Model Finetuning

  Supports advanced finetuning techniques like LoRA, QLoRA, and reinforcement learning with out-of-the-box tools.

• Custom Docker and Networking

  Optimized Docker implementation for faster cold starts and a custom Istio-based networking layer for multi-node GPU inference and training.

• Developer Productivity Tools

  GPU devcontainers with hot reloading enable rapid experimentation directly on GPUs without complex setup.

Use Cases

• AI Model Deployment : Deploy custom AI models quickly on your private cloud with autoscaling serverless GPUs.
• Generative AI Applications : Run inference and batch jobs for generative AI models like Llama3, Qwen, and Stable Diffusion efficiently.
• Model Finetuning and Training : Perform serverless training and fine-tuning of large models using advanced techniques without managing environments.
• Cost-Effective Cloud GPU Usage : Reduce cloud GPU expenses by up to 30% through intelligent autoscaling and efficient resource management.
• DevOps Automation : Automate deployment workflows with GitHub Actions integration and simplify infrastructure management.

FAQs