Reputation: 3671
I am following the reference from the following page:
https://tfhub.dev/google/universal-sentence-encoder/4
In the code the model is loaded from the internet with the following code:
import tensorflow as tf
embed = hub.load("https://tfhub.dev/google/universal-sentence-encoder/4")
I would like to be able to load a model I have saved in my local directory
For example:
embed = hub.Module('data\models\universal-sentence-encoder_4.tar.gz')
This code returns the following error
RuntimeError: Missing implementation that supports: loader
How can this be done?
Upvotes: 3
Views: 913
Reputation: 3671
The Issue was that the file was not unzipped.
After unzipping, the directory path was pointed to the unzip content location, with no file name specified.
Also the Module
method was changed to load
the code below works, assuming the unzipped embedding model .pb file and accompanying folders are located in the specified directory.
embed = hub.load('data\models\')
Upvotes: 3