Skip to main content

​
Scripted testing

A shell script is available that runs all of the steps below automatically using mock model files. Download model_repo_testing.sh from the internal Notion page and run it to validate end-to-end without manually executing each step.

​
Manual testing

​
Prerequisites

  • Your email is feature-flagged for Model Repo access.
  • The following environment variables are exported:
export RUNPOD_API_URL="https://rest.runpod.io/v1"
export RUNPOD_GRAPHQL_URL="https://api.runpod.io/graphql"
export RUNPOD_API_KEY="your-api-key"

export MODEL_NAME="$(whoami)-test-$(date +%s)"  # must be unique per test run
export MODEL_PATH="/path/to/model"
  • MODEL_NAME should be unique for each test run. Reusing the same name uploads a new version of the existing model rather than creating a new one.
  • jq is installed for parsing JSON output.

​
Step 1: Install Go

Building runpodctl requires Go: 
brew install go

​
Step 2: Build runpodctl

git clone git@github.com:runpod/runpodctl.git
cd runpodctl
make

​
Step 3: Upload the model

./bin/runpodctl model add \
  --name "$MODEL_NAME" \
  --model-path "$MODEL_PATH" \
  --create-upload
This outputs a JSON string listing all uploaded files.

​
Step 4: Wait for the model to be hashed

After upload, the model must be hashed by an asynchronous background process. This typically completes in a few minutes but can take up to 10–15 minutes. Poll until the hash field is non-null: 
./bin/runpodctl model list --name "$MODEL_NAME" | jq -r '.[0].versions[0].hash'
While hashing is in progress, the command returns null: 
% ./bin/runpodctl model list --name "$MODEL_NAME" | jq -r '.[0].versions[0].hash'
null
Once hashing is complete, it returns the hash value: 
% ./bin/runpodctl model list --name "$MODEL_NAME" | jq -r '.[0].versions[0].hash'
71a311bdf0ca44119ed74dbef8cf573bc89b58cbc48a10fe508f756ebb1922dc

​
Step 5: Build the model URL

export USER_ID="$(./bin/runpodctl user | jq -r '.id')"
export MODEL_HASH="$(./bin/runpodctl model list --name "$MODEL_NAME" | jq -r '.[0].versions[0].hash')"
export MODEL_URL="https://local/${USER_ID}/${MODEL_NAME}:${MODEL_HASH}"

​
Step 6: Deploy a Serverless endpoint with the model attached

./bin/runpodctl serverless create \
  --name "$(whoami)_ctl_test" \
  --template-id "mockworker" \
  --gpu-id "AMPERE_24" \
  --workers-max 3 \
  --workers-min 1 \
  --model-reference "$MODEL_URL"
Notes:
  • --model-reference is only supported with --template-id and GPU endpoints.
  • --gpu-id accepts a single GPU ID — do not pass a comma-separated list.
  • --model-reference is repeatable if multiple models need to be attached.

​
Step 7: Verify the model is attached to the worker

  1. Go to Serverless in the left navigation bar under Resources.
  2. Select the endpoint you created (ctl_test if you used the commands above).
  3. Click the Workers tab.
  4. Select a worker showing a Running status.
  5. Click Connect, then use the ssh command or the Web Terminal.
  6. Run the following to confirm your model files are present:
find /runpod-volume/huggingface-cache/hub/models--$(echo $MODEL_NAME | sed 's@/@--@g')/snapshots/${MODEL_REVISION} -type f
There is currently no way to retrieve SSH connection details for a running Serverless worker via runpodctl. Use the web UI to connect.

​
Step 8: Clean up

Delete the endpoint after testing to stop spend. Use the web UI or: 
./bin/runpodctl serverless delete <endpoint-id>