Warning
For Artifactory versions earlier than 7.75.3, It is only possible to deploy lighter models to Hugging Face local repositories due to limitations in the implementation of the Hugging Face client.
This topic describes how to deploy Hugging Face models and datasets to an Artifactory repository. Artifactory supports resolving datasets starting from version 7.90.x.
To deploy models or datasets to Artifactory using the huggingface_hub
library insert your folder name, name, and revision number into the following command and run it:
Note
Make sure to replace the placeholders in angle brackets (<>) with your own model/dataset source folder name, name, and unique identifier.
Warning
Deploying a model or dataset using the same UUID as a cached model/dataset will cause the new one to override and replace the previous one.
from huggingface_hub import HfApi api = HfApi() api.upload_folder( folder_path="<MODEL/DATASET_SOURCE_FOLDER_NAME>", # Enter the name of the folder on your local machine where your model resides. repo_id="<MODEL/DATASET_NAME>", # Enter the name of the model, following the Hugging Face repository naming structure 'organization/name'. (models--$<MODEL_NAME>) revision="<MODEL/DATASET_UUID>", # Enter a unique identifier for your model. We recommend using a git commit revision ID. (snapshots/$<REVISION_NAME>/...files) repo_type="model"/"dataset" )
For example:
from huggingface_hub import HfApi api = HfApi() api.upload_folder( folder_path="vit-base-patch16-224", # Enter the name of the folder on your local machine where your model resides.folder to upload location on the FS repo_id="nsi319/legalpegasus", # Enter the name of the model, following the Hugging Face repository naming structure 'organization/name'. (models--$<MODEL_NAME>) revision="54ef2872d33bbff28eb09544bdecbf6699f5b0b8", # Enter a unique identifier for your model. We recommend using a Git commit revision ID. (snapshots/$<REVISION_NAME>/...files) repo_type="model" )