Whisper Video Transfer and GPU Processing Plan | Generated by AI

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Question: I have a video file “meeting_01 2.mp4” and an RTX 4070 GPU machine at 192.168.1.36. What’s the best plan to transfer the video there and run Whisper with GPU acceleration?

Answer:

Plan Overview

Here’s what needs to happen end-to-end:

Step 1 — Locate the video on this machine

Find where meeting_01 2.mp4 lives (likely ~/Downloads/ or similar).

Step 2 — Transfer the video to the remote machine

Use scp (or rsync) to copy it over your LAN:

scp "~/Downloads/meeting_01 2.mp4" lzw@192.168.1.36:~/projects/whisper-test/

Note: The space in the filename needs quoting.

Step 3 — SSH into the remote machine and set up the project

ssh lzw@192.168.1.36
mkdir -p ~/projects/whisper-test
cd ~/projects/whisper-test
pip install openai-whisper

Step 4 — Run Whisper with CUDA (RTX 4070)

whisper "meeting_01 2.mp4" --model large --device cuda --output_dir ~/projects/whisper-test/

Expected time: ~2–3 minutes for a 2-hour video on RTX 4070.


What I Can and Cannot Do Here

Task Feasible? Why
Find the file on this machine Can search local filesystem
Run scp / ssh to remote No network access to 192.168.1.36 (private LAN) from this sandbox
Create project folder remotely Same reason — private LAN not reachable
Generate a ready-to-run shell script Can write it for you to execute yourself

I can produce a single setup_whisper.sh script that does all steps automatically when you run it on your local machine:

  1. Finds the video file
  2. Creates the remote project directory via SSH
  3. Transfers the file via scp
  4. Installs Whisper remotely
  5. Runs Whisper with --device cuda

Just say “yes, generate the script” and I’ll produce it ready to go.

Note: You’ll need SSH key auth or be ready to type the password a couple of times.


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