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Copy file name to clipboardExpand all lines: articles/cognitive-services/openai/concepts/models.md
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@@ -43,7 +43,7 @@ Azure OpenAI's model names typically correspond to the following standard naming
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|`{input-type}`| ([Embeddings models](#embeddings-models) only) The input type of the embedding supported by the model. For example, text search embedding models support `doc` and `query`.|
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|`{identifier}`| The version identifier of the model. |
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For example, our most powerful GPT-3 model is called `text-davinci-002`, while our most powerful Codex model is called `code-davinci-002`.
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For example, our most powerful GPT-3 model is called `text-davinci-003`, while our most powerful Codex model is called `code-davinci-002`.
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> Older versions of the GPT-3 models are available, named `ada`, `babbage`, `curie`, and `davinci`. These older models do not follow the standard naming conventions, and they are primarily intended for fine tuning. For more information, see [Learn how to customize a model for your application](../how-to/fine-tuning.md).
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-`text-ada-001`
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-`text-babbage-001`
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-`text-curie-001`
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-`text-davinci-002`
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-`text-davinci-003`
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While Davinci is the most capable, the other models provide significant speed advantages. Our recommendation is for users to start with Davinci while experimenting, because it will produce the best results and validate the value our service can provide. Once you have a prototype working, you can then optimize your model choice with the best latency/performance balance for your application.
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| Davinci*| Yes | No | N/A | East US, South Central US, West Europe |
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| Text-davinci-001 | Yes | No | South Central US, West Europe | N/A |
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| Text-davinci-002 | Yes | No | East US, South Central US, West Europe | N/A |
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| Text-davinci-003 | Yes | No | East US | N/A |
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| Text-davinci-fine-tune-002*| Yes | No | N/A | East US, West Europe |
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\*Models available by request only. Please open a support request.
Copy file name to clipboardExpand all lines: articles/cognitive-services/openai/includes/studio.md
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## Deployments
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Before you can generate text or inference, you need to deploy a model. This is done by selecting the **create new deployment** on the deployments page. From here, you can select from one of our many available models. For getting started we recommend `text-davinci-002`.
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Before you can generate text or inference, you need to deploy a model. This is done by selecting the **create new deployment** on the deployments page. From here, you can select from one of our many available models. For getting started we recommend `text-davinci-003`.
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Once this is complete, select the 'Playground' button on the left nav to start experimenting.
Copy file name to clipboardExpand all lines: articles/cognitive-services/openai/quotas-limits.md
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| Limit Name | Limit Value |
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|--|--|
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| OpenAI resources per region | 2 |
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| Requests per second per deployment | 20 requests per second for: text-davinci-002, text-davinci-fine-tune-002, code-cushman-002, code-davinci-002, code-davinci-fine-tune-002 <br ><br> 50 requests per second for all other text models.
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| Requests per second per deployment | 20 requests per second for: text-davinci-003, text-davinci-002, text-davinci-fine-tune-002, code-cushman-002, code-davinci-002, code-davinci-fine-tune-002 <br ><br> 50 requests per second for all other text models.
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|
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| Max fine-tuned model deployments | 2 |
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| Ability to deploy same model to multiple deployments | Not allowed |
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