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You should see the lambda-stack image in the list, this is the one we will use for now.

To start a program in the a container using this image, use the docker run --rm command:

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Add packages to the container

The container image may not have all the packages you need. To add more packages, you can create a new container image based on the LambdaStack one.

To create a container image, you need a Dockerfile definition file. It contains the information about the base container image and the installations installation instructions for the additional packages.

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FROM lambda-stack:20.04
RUN pip install pip install transformers[torch]

To build the corresponding container image, first create an empty folder and save the Dockerfile in it:

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then use the docker build command to generate the new container image:

$ cd hugging_container
$ docker build -t pytorch-transformers .

The -t flag is used to tag the container image, making it easier to find and use it later.

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You can now use it in place of the LambdaStack containerimage:

$ docker run --rm pytorch-transformers \
    python -c "from transformers import pipeline; print(pipeline('sentiment-analysis')('I love you'))"
libibverbs: Warning: couldn't open config directory '/etc/libibverbs.d'.
libibverbs: Warning: couldn't open config directory
'/etc/libibverbs.d'.
No model was supplied, defaulted to distilbert-base-uncased-finetuned-sst-2-english and revision af0f99b (https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english).
Using a pipeline without specifying a model name and revision in production is not recommended.
Downloading config.json: 100%|██████████| 629/629 [00:00<00:00, 1.45MB/s]
Downloading pytorch_model.bin: 100%|██████████| 255M/255M [00:10<00:00, 24.5MB/s]
Downloading tokenizer_config.json: 100%|██████████| 48.0/48.0 [00:00<00:00, 72.8kB/s]
Downloading vocab.txt: 100%|██████████| 226k/226k [00:00<00:00, 295kB/s]
[{'label': 'POSITIVE', 'score': 0.9998656511306763}]

Containers Container images can be deleted using the docker image rm command. For example, remove the pytorch-transformers container image as follows:

$ docker image rm pytorch-transformers
Untagged: pytorch-transformers:latest
Deleted: sha256:432c6be0a999484db090c5d9904e5c783454080d8ad8bc39e0499ace479c4559
Deleted: sha256:623ae3b33709c2fc4c40bc2c3959049345fee0087d39b4f53eb95aefd1c16f7d

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