AI Studio
What is AI Studio?
AI Studio is an end-to-end platform that empowers developers, researchers, and enterprises to explore, fine-tune, evaluate, and deploy large AI models—without the hassle of managing infrastructure or engineering complexity.
Whether you're experimenting with foundational models, adapting them to your domain, or scaling them for production—AI Studio provides everything in one place.
Why AI Studio?
Today’s AI demands go beyond access to pre-trained models. Organizations need infrastructure flexibility, customization workflows, and robust evaluation capabilities. AI Studio addresses this with:
Curated Model Catalog: Access top-performing models in text, vision, speech, and multimodal domains.
No-Code Fine-Tuning: Customize models with your data using efficient techniques like LoRA.
Integrated Evaluation: Benchmark functional and performance metrics before deployment.
Scalable Deployment: Launch models on-demand or via dedicated endpoints with GPU-backed infrastructure.
Core Capabilities
Model Catalog
Browse a curated selection of foundational and fine-tuned models.
Each model card includes:
Overview and intended use cases
Licensing and attribution
GitHub repository links (if available)
API model string and sample usage
Interactive playground for real-time experimentation
Inferencing
Run inference directly on models using APIs or the playground.
Control parameters such as:
temperature,top_p,max_tokens,logit_bias, etc.
Transparent, token-based pay-as-you-go pricing.
Fine-Tuning
Fine-tune models such as Llama-3 and Mistral using LoRA adapters.
Upload datasets in
instruction,input,outputJSON format.Monitor checkpoint progress and deploy fine-tuned versions directly.
Supports customization for specific domains such as healthcare, legal, or customer support.
Evaluation
Model Evaluation:
Evaluate task performance using datasets such as MMLU, BoolQ, HellaSwag, GSM8k, and TruthfulQA.
Multi-language support, including Indic languages.
Metrics include accuracy, relevance, and ethicality.
Performance Evaluation:
Measure latency (TTFT, inter-token, end-to-end), throughput, and token counts.
Configure test load parameters such as concurrency, input/output token length, etc.
Compare evaluation runs across models and versions.
Deployment
On-Demand Deployment:
Quick, pay-per-use deployment for experimentation or low-volume tasks.
Dedicated Deployment:
Persistent endpoints using dedicated GPUs like NVIDIA H100.
Recommended for high-availability production use cases.
Deployment cost is based on GPU time usage.
Management Features:
Monitor deployment status
Bring down unused deployments to avoid unnecessary costs
Who is AI Studio For?
Developers & Engineers: Build and integrate AI-powered features quickly using APIs and SDKs.
Researchers & Data Scientists: Experiment with model architectures and datasets without infrastructure setup.
Product & Business Teams: Evaluate and compare models to inform decisions about product integration.
How It Works
Explore the Model Catalog and try out models in the playground or via API.
Fine-Tune a model using your own dataset if needed.
Evaluate both task and performance metrics using built-in tools.
Deploy the best model variant with on-demand or persistent infrastructure.
Monitor usage, costs, and metrics to ensure ongoing optimization.
Key Advantages
End-to-end AI model lifecycle support in a single platform
Access to top open-source and proprietary models
Efficient and scalable fine-tuning using LoRA
Built-in evaluation with task and operational metrics
Flexible deployment and billing options
Developer-friendly experience with interactive playgrounds and starter code
Next Steps
Get Started with Quickstart
Browse the Model Catalog
Fine-Tune Your First Model
Evaluate Your Model
Deploy to Production
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