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Install fedml library on your machine

pip install fedml

Create a model from Hugging Face

Use fedml model create command to create a model. For options, use -n to indicate the model card name, then use -m to indicate a pre-built model.

In this quick start example, we will try to deploy an EleutherAI/pythia-70m model from Hugging Face. To use a hugging face model, you will need to use hf: as the prefix of the model name. So the full model name is hf:EleutherAI/pythia-70m.

fedml model create -n hf_model -m hf:EleutherAI/pythia-70m

Deploy the model to the local machine

Use fedml model deploy command to deploy the model. Use -n to indicate the model card name. To deploy to the local machine, use --local option.

fedml model deploy -n hf_model --local

Above command will:

  1. Automatically download and install the dependencies for inference.
  2. Download the model weights from Hugging Face.
  3. Start the model inference server and listen to localhost:2345/predict for requests.
Executing bootstrap script ...
Bootstrap start...
+ pip install langchain

Bootstrap finished
Bootstrap script is executed successfully!

INFO: Started server process [29013]
INFO: Waiting for application startup.
INFO: Application startup complete.
INFO: Uvicorn running on (Press CTRL+C to quit)

Use a curl command to test the inference server.

curl -XPOST localhost:2345/predict -d '{"text": "Hello"}'

You should see the output from the terminal with the response of that model.

"{'generated_text': '...'}"

Deploy the model to Serverless GPU cloud


Before you start, you will need to create an account on FedML Nexus AI Cloud. After you create an account, you will see an Account Key (API Key) from the profile page. getApiKey.jpg

Next you need to bind your credit card to your account. This is required to use the GPU cloud. payment.jpg

Use fedml login $api_key to login to Nexus AI Cloud. Replace $api_key with your own API key.

fedml login $api_key

Use fedml model deploy command to deploy the model. Use -n to indicate the model card name.

fedml model deploy -n hf_model