Using GPT-2 on Azure OpenAI

Implementation guide · GPT-2 · OpenAI

Provisioned

Quick Start

1
Create an account at Azure OpenAI and generate an API key.
2
Use the Azure OpenAI SDK or REST API to call gpt2 — see the documentation for request format.

API Portal Documentation Pricing Model Card

Code Examples

Install

pip install openai

API key

AZURE_OPENAI_API_KEY

Model ID

gpt2

gpt2 is your Azure deployment name, not the underlying model name. Deployment names are set when you deploy a model in Azure AI Foundry / Azure OpenAI Studio.

import os
from openai import AzureOpenAI

client = AzureOpenAI(
    azure_endpoint=os.environ["AZURE_OPENAI_ENDPOINT"],  # e.g. https://{resource}.openai.azure.com
    api_key=os.environ["AZURE_OPENAI_API_KEY"],
    api_version="2024-02-01"
)
response = client.chat.completions.create(
    model="gpt2",  # your deployment name
    messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)

About Azure OpenAI

Azure OpenAI Service hosts OpenAI's GPT-4o, GPT-4, GPT-3.5, and embedding models on Microsoft Azure with enterprise SLAs. Deployments run in customer-selected regions with private networking, role-based access control, and capacity options spanning Standard pay-per-token, Provisioned Throughput Units (PTUs) for reserved capacity, Global Standard shared capacity, and Batch processing. Azure OpenAI sits inside the wider Microsoft Foundry / Azure AI Studio control plane, which adds an evaluation, monitoring, and Agent Service layer on top of the base model APIs. For workloads that need non-OpenAI models (Claude, DeepSeek, Grok, Llama, Mistral, NVIDIA Nemotron), Microsoft Foundry is the broader catalog; Azure OpenAI is the OpenAI-specific entry point. The service is API-compatible with the OpenAI SDK in most flows, so teams typically swap base URLs and authentication rather than rewriting calls.

Azure OpenAI Service hosts OpenAI's GPT-4o, GPT-4, GPT-3.5, and embedding models on Microsoft Azure with enterprise SLAs. Microsoft's broader AI platform spans Azure Machine Learning, Azure Cognitive Services, and Azure AI Search, plus productivity tools like Microsoft 365 Copilot and developer tooling in Visual Studio and the .NET framework. The platform emphasizes responsible AI, security, and regional compliance.

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