Using CodeLlama 7B Python on Microsoft Foundry
Implementation guide · Code Llama · AI at Meta
Quick Start
- 1
- 2Use the Microsoft Foundry SDK or REST API to call
codellama-7b-python— see the documentation for request format. - 3
Code Examples
About Microsoft Foundry
Microsoft Foundry offers a comprehensive platform-as-a-service for enterprise AI operations. It provides multiple deployment options including Serverless APIs (pay-as-you-go), Global Standard (shared managed capacity), Provisioned Throughput Units (reserved capacity), batch processing, and bring-your-own model deployments. The platform features a unified control plane for models, agents, tools, and observability. Its Agent Service enables building and deploying AI agents with built-in tracing, monitoring, and governance. Evaluation and monitoring tools assess model performance, safety, and groundedness. Foundry supports seamless upgrades from Azure OpenAI with non-destructive migration, maintaining existing deployments while unlocking multi-provider model access and advanced platform capabilities.
Microsoft Foundry is a unified Azure platform-as-a-service offering for enterprise AI operations, model builders, and application development. It provides access to over 1,900 models from Microsoft, OpenAI, Anthropic, Mistral, xAI, Meta, DeepSeek, Hugging Face, and more. Foundry unifies agents, models, and tools under a single management grouping with built-in enterprise-readiness capabilities including tracing, monitoring, evaluations, and customizable enterprise setup configurations.
Pricing on Microsoft Foundry
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.52 |
| Output tokens | $0.67 |
Capabilities
About CodeLlama 7B Python
CodeLlama 7B Python is a specialized variant of Meta's CodeLlama family, designed for Python programming tasks. With 7 billion parameters, it excels in code completion, infilling, and instruction following. The model utilizes an optimized auto-regressive transformer architecture and has been trained on diverse programming tasks. It's suitable for both commercial and research applications, offering AI engineers a powerful tool for enhancing productivity in Python-centric environments. For more details, visit the model's page on Hugging Face .