finetune_steps
parameter.
👍 Use an Azure AI endpoint To use an Azure AI endpoint, remember to set also thebase_url
argument:nixtla_client = NixtlaClient(base_url="you azure ai endpoint", api_key="your api_key")
📘 Available models in Azure AI If you are using an Azure AI endpoint, please be sure to setBy default, only a small amount of finetuning is applied (model="azureai"
:nixtla_client.forecast(..., model="azureai")
For the public API, we support two models:timegpt-1
andtimegpt-1-long-horizon
. By default,timegpt-1
is used. Please see this tutorial on how and when to usetimegpt-1-long-horizon
.
finetune_depth=1
). We can increase the intensity of finetuning by
increasing the finetune_depth
parameter. Note that increasing
finetune_depth
and finetune_steps
increases wall time for generating
predictions.