Below are the providers that are supported to directly load the model file into Inferless
  • AWS S3
  • Google Cloud Buckets
  • Azure File Storage
Before you upload your custom model, make sure you go through and follow the prerequisites conditions mentioned below.

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File structure requirements

The below format should be kept in mind while loading your code to Inferless from cloud providers. The model file has to be loaded as a ZIP file. The structure of the model file that is to be loaded is described below based on the framework used. The model names has to be in the format as given in the example below.
PyTorch - File structure
/
├── config.pbtxt
├── 1
│   ├── model.pt

#*Any other file can be added along with the above structure and files for any dependencies in the model*

  • ​
    TensorFlow

TensorFlow - Structure
/
├── 1
│   ├── model.savedmodel
│   │   ├── saved_model.pb

#*Any other file can be added along with the above structure and files for any dependencies in the model*
ONNX - File Structure
/
├── config.pbtxt
├── 1
│   ├── model.onnx

#*Any other file can be added along with the above structure and files for any dependencies in the model*
Once you have made sure the model file structure is in the right format, you can upload the model from your cloud storage to Inferless using the “Import Model” option
  • Click here for steps to upload