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    deepseek-ai/deepseek-r1

    API Reference

    Deploy

    Ready to scale? Choose your deployment path.
    Deploying your application in production? Get started with a 90-day evaluation of NVIDIA AI Enterprise

    Follow the steps below to download and run the NVIDIA NIM inference microservice for this model on your infrastructure of choice.

    Follow the steps below to download and run the NVIDIA NIM inference microservice with NIM Operator on your infrastructure of choice.

    Step 1
    Install the NIM Operator

    • Prerequisites
      • Install the NVIDIA GPU Operator
      • Generate API Key
    helm repo add nvidia https://helm.ngc.nvidia.com/nvidia \
       && helm repo update
    
    helm install nim-operator nvidia/k8s-nim-operator --create-namespace -n nim-operator
    

    Step 2
    Create a ImagePull Secrets

    kubectl create secret -n nim-service docker-registry ngc-secret \
        --docker-server=nvcr.io \
        --docker-username='$oauthtoken' \
        --docker-password=<PASTE_API_KEY_HERE>
    
    kubectl create secret -n nim-service generic ngc-api-secret \
        --from-literal=NGC_API_KEY=<PASTE_API_KEY_HERE>
    

    Step 3
    Create a NIM Cache with Available storage class on the Cluster

    apiVersion: apps.nvidia.com/v1alpha1
    kind: NIMCache
    metadata:
      name: deepseek-ai-deepseek-r1
    spec:
      source:
        ngc:
          modelPuller: nvcr.io/nim/deepseek-ai/deepseek-r1:latest
          pullSecret: ngc-secret
          authSecret: ngc-api-secret
          model:
            engine: tensorrt_llm
            tensorParallelism: "1"
      storage:
        pvc:
          create: true
          storageClass: <storage-class-name>
          size: "50Gi"
          volumeAccessMode: ReadWriteMany
      resources: {}
    

    Step 4
    Create a NIM Service

    apiVersion: apps.nvidia.com/v1alpha1
    kind: NIMService
    metadata:
      name: deepseek-ai-deepseek-r1
    spec:
      image:
        repository: nvcr.io/nim/deepseek-ai/deepseek-r1
        tag: 1.8.3
        pullPolicy: IfNotPresent
        pullSecrets:
          - ngc-secret
      authSecret: ngc-api-secret
      storage:
        nimCache:
          name: deepseek-ai-deepseek-r1
          profile: ''
      replicas: 1
      resources:
        limits:
          nvidia.com/gpu: 1
      expose:
        service:
          type: ClusterIP
          port: 8000
    

    Step 5
    Test the Deployed NIM

    kubectl run --rm -it -n default curl --image=curlimages/curl:latest -- ash
    
    curl -X "POST" \
     'http://deepseek-ai-deepseek-r1.nim-service:8000/v1/chat/completions' \
      -H 'Accept: application/json' \
      -H 'Content-Type: application/json' \
      -d '{
            "model": "deepseek-ai/deepseek-r1",
            "messages": [
            {
              "content":"What should I do for a 4 day vacation at Cape Hatteras National Seashore?",
              "role": "user"
            }],
            "top_p": 1,
            "n": 1,
            "max_tokens": 1024,
            "stream": false,
            "frequency_penalty": 0.0,
            "stop": ["STOP"]
          }'
    

    For more details on getting started with this NIM, visit the NVIDIA NIM Operator Docs.

    Specifications

    State-of-the-art, high-efficiency LLM excelling in reasoning, math, and coding.

    • Math
    • advanced reasoning
    • chat
    Provider
    DeepSeek AI
    Last Modified
    1 year ago

    Model Availability

    Free Endpoint
    Deprecated
    Partner Endpoint
    Not available
    Download Available
    Available