Adding an example of NIM

examples/deployment/nim/README.md

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+# NIM
+
+This example shows how to deploy `Meta/LLama3-8b-instruct` with `dstack` using [NIM :material-arrow-top-right-thin:{ .external }](https://docs.nvidia.com/nim/large-language-models/latest/getting-started.html).
+
+??? info "Prerequisites"
+    Once `dstack` is [installed](https://dstack.ai/docs/installation), go ahead clone the repo, and run `dstack init`.
+
+    <div class="termy">
+
+    ```shell
+    $ git clone https://github.com/dstackai/dstack
+    $ cd dstack
+    $ dstack init
+    ```
+
+    </div>
+
+## Deployment
+
+### Running as a task
+If you'd like to run Meta/Llama 3-8b for development purposes, consider using `dstack` [tasks](https://dstack.ai/docs/tasks/).
+
+<div editor-title="examples/deployment/nim/task.dstack.yml">
+
+```yaml
+type: task
+
+name: llama3-nim-task
+image: nvcr.io/nim/meta/llama3-8b-instruct:latest
+
+env:
+  - NGC_API_KEY
+registry_auth:
+  username: $oauthtoken
+  password: ${{ env.NGC_API_KEY }}
+
+ports: 
+  - 8000
+
+spot_policy: auto
+
+resources:
+  gpu: 24GB
+
+backends: ["aws", "azure", "cudo", "datacrunch", "gcp", "lambda", "oci", "tensordock"]
+```
+</div>
+Note, Currently NIM is supported on every backend except RunPod and Vast.ai.
+
+### Deploying as a service
+
+If you'd like to deploy the model as an auto-scalable and secure endpoint,
+use the [service](https://dstack.ai/docs/services) configuration. You can find it at [`examples/deployment/nim/service.dstack.yml` :material-arrow-top-right-thin:{ .external }](https://github.com/dstackai/dstack/blob/master/examples/deployment/nim/service.dstack.yml)
+
+### Running a configuration
+
+To run a configuration, use the [`dstack apply`](https://dstack.ai/docs/reference/cli/index.md#dstack-apply) command. 
+
+<div class="termy">
+
+```shell
+$ NGC_API_KEY=...
+
+$ dstack apply -f examples/deployment/nim/task.dstack.yml
+
+ #  BACKEND  REGION             RESOURCES                 SPOT  PRICE       
+ 1  gcp      asia-northeast3    4xCPU, 16GB, 1xL4 (24GB)  yes   $0.17   
+ 2  gcp      asia-east1         4xCPU, 16GB, 1xL4 (24GB)  yes   $0.21   
+ 3  gcp      asia-northeast3    8xCPU, 32GB, 1xL4 (24GB)  yes   $0.21 
+
+Submit the run llama3-nim-task? [y/n]: y
+
+Provisioning...
+---> 100%
+```
+</div>
+
+
+## Source code
+
+The source-code of this example can be found in 
+[`examples/deployment/nim` :material-arrow-top-right-thin:{ .external }](https://github.com/dstackai/dstack/blob/master/examples/deployment/nim).
+
+## What's next?
+
+1. Check [dev environments](https://dstack.ai/docs/dev-environments), [tasks](https://dstack.ai/docs/tasks), 
+   [services](https://dstack.ai/docs/services), and [protips](https://dstack.ai/docs/protips).
+2. Browse [Available models in NGC Catalog :material-arrow-top-right-thin:{ .external }](https://catalog.ngc.nvidia.com/containers?filters=nvidia_nim%7CNVIDIA+NIM%7Cnimmcro_nvidia_nim&orderBy=scoreDESC&query=&page=&pageSize=).

examples/deployment/nim/service.dstack.yml

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+type: service
+
+image: nvcr.io/nim/meta/llama3-8b-instruct:latest
+
+env:
+  - NGC_API_KEY
+registry_auth:
+  username: $oauthtoken
+  password: ${{ env.NGC_API_KEY }}
+
+port: 8000
+
+spot_policy: auto
+
+resources:
+  gpu: 24GB
+
+backends: ["aws", "azure", "cudo", "datacrunch", "gcp", "lambda", "oci", "tensordock"]

examples/deployment/nim/task.dstack.yml

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+type: task
+
+name: llama3-nim-task
+image: nvcr.io/nim/meta/llama3-8b-instruct:latest
+
+env:
+  - NGC_API_KEY
+registry_auth:
+  username: $oauthtoken
+  password: ${{ env.NGC_API_KEY }}
+
+ports:
+  - 8000
+
+spot_policy: auto
+
+resources:
+  gpu: 24GB
+
+backends: ["aws", "azure", "cudo", "datacrunch", "gcp", "lambda", "oci", "tensordock"]