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print_color "green" "Connection scripts saved in /workspace/connect_windows.bat and /workspace/connect_linux.sh"
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EOF
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To quickly set up password-based SSH, run this command to download and execute a [helper script](https://github.com/justinwlin/Runpod-SSH-Password/blob/main/passwordrunpod.sh) for password setup:
@@ -296,7 +141,7 @@ While SSH operates on port 22 within your Pod, Runpod assigns a different extern
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If you see the message `Environment variables RUNPOD_PUBLIC_IP or RUNPOD_TCP_PORT_22 are missing` when running the script, it means one or more of the required environment variables are not set. Please ensure you have met all the necessary requirements described above.
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</Warning>
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After pasting the script into your terminal and entering a password, you'll see example commands for SSH or SCP which you can use to connect to your Pod and transfer files from your local machine:
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After running the script and entering a password, you'll see example commands for SSH or SCP which you can use to connect to your Pod and transfer files from your local machine:
Copy file name to clipboardExpand all lines: pods/manage-pods.mdx
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@@ -31,6 +31,24 @@ GPU configuration:
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4. Specify your **GPU count** if you need multiple GPUs.
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5. Click **Deploy On-Demand** to deploy and start your Pod.
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<Warning>
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**CUDA Version Compatibility**
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When using templates (especially community templates like `runpod/pytorch:2.8.0-py3.11-cuda12.8.1-cudnn-devel-ubuntu22.04`), ensure the host machine's CUDA driver version matches or exceeds the template's requirements.
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If you encounter errors like "OCI runtime create failed" or "unsatisfied condition: cuda>=X.X", you need to filter for compatible machines:
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1. Click **Additional filters** in the Pod creation interface
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2. Click **CUDA Versions** filter dropdown
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3. Select a CUDA version that matches or exceeds your template's requirements (e.g., if the template requires CUDA 12.8, select 12.8 or higher)
**Note:** Check the template name or documentation for CUDA requirements. When in doubt, select the latest CUDA version as newer drivers are backward compatible.
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</Warning>
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CPU configuration:
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1. Select a **CPU type** (e.g., CPU3/CPU5, Compute Optimized, General Purpose, Memory-Optimized).
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