TensorFlow Hub is a library for reusable machine learning modules.
!pip install "tensorflow_hub==0.4.0"
!pip install "tf-nightly"
import tensorflow as tf
import tensorflow_hub as hub
tf.enable_eager_execution()
module_url = "https://tfhub.dev/google/tf2-preview/nnlm-en-dim128/1"
embed = hub.KerasLayer(module_url)
embeddings = embed(["A long sentence.", "single-word",
"http://example.com"])
print(embeddings.shape) #(3,128)
TensorFlow Hub is a library for the publication, discovery, and consumption of reusable parts of machine learning models. A module is a self-contained piece of a TensorFlow graph, along with its weights and assets, that can be reused across different tasks in a process known as transfer learning. Transfer learning can:
- Train a model with a smaller dataset,
- Improve generalization, and
- Speed up training.
