From bc2d19995255ee18ef7878b164c854106684c837 Mon Sep 17 00:00:00 2001 From: guarin <43336610+guarin@users.noreply.github.com> Date: Fri, 16 Aug 2024 10:13:09 +0200 Subject: [PATCH] Remove LightlySSL in Three Lines Docs (#1636) * Remove outdated docs --- .../getting_started/lightly_at_a_glance.rst | 22 +------------------ 1 file changed, 1 insertion(+), 21 deletions(-) diff --git a/docs/source/getting_started/lightly_at_a_glance.rst b/docs/source/getting_started/lightly_at_a_glance.rst index ed1eee06f..ba9d04ac7 100644 --- a/docs/source/getting_started/lightly_at_a_glance.rst +++ b/docs/source/getting_started/lightly_at_a_glance.rst @@ -221,28 +221,8 @@ Furthermore, the ResNet backbone can be used for transfer and few-shot learning. on a folder 'cats' with subfolders 'Maine Coon', 'Bengal' and 'British Shorthair' Lightly\ **SSL** automatically returns the enumerated labels as a list. -Lightly\ **SSL** in Three Lines --------------------------- -Lightly\ **SSL** also offers an easy-to-use interface. The following lines show how the package can -be used to train a model with self-supervision and create embeddings with only three lines -of code. - -.. code-block:: python - - from lightly.core import train_embedding_model, embed_images - - # first we train our model for 10 epochs - checkpoint = train_embedding_model(input_dir='./my/cute/cats/dataset/', trainer={'max_epochs': 10}) - - # let's embed our 'cats' dataset using our trained model - embeddings, labels, filenames = embed_images(input_dir='./my/cute/cats/dataset/', checkpoint=checkpoint) - - # now, let's inspect the shape of our embeddings - print(embeddings.shape) - - -What's next? +What's Next? ------------ Get started by :ref:`rst-installing` and follow through the tutorials to learn how to get the most out of using Lightly: