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Update README.md: Revise installation instructions and clarify platform-specific run commands

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Kristofer Söderström
2026-03-02 17:04:59 +01:00
parent f8cf42733d
commit acb6947f87
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README.md
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@@ -32,10 +32,10 @@ Or by cloning the repository with:
```
git clone https://github.com/soderstromkr/transcribe.git
```
### Python Version **(any platform including Mac users)**
1. Install Python 3.10 or later. You can download it from [python.org](https://www.python.org/downloads/). During installation, **check "Add Python to PATH"**. No administrator rights are needed if you install for your user only.
### Prerequisites
1. Install **Python 3.10 or later** from [python.org](https://www.python.org/downloads/). During installation, **check "Add Python to PATH"**. No administrator rights are needed if you install for your user only.
2. Run the installer. Open a terminal (Command Prompt on Windows, Terminal on Mac/Linux) in the project folder and run:
2. Run the installer. Open a terminal in the project folder and run:
```
python install.py
```
@@ -46,14 +46,16 @@ This will:
Alternatively, you can install manually with `pip install -r requirements.txt`.
3. Run the app:
1. For **Windows**: double-click `run_Windows.bat` (it will auto-install on first run) or run:
### Run on Windows
Double-click `run_Windows.bat` (it will auto-install on first run) or run:
```
python app.py
```
2. For **Mac / Linux**: run `./run_Mac.sh` (auto-installs on first run). See [Mac instructions](Mac_instructions.md) for details.
**Note** The first run with a given model will download it (~75 MB for base, ~500 MB for medium). After that, everything works offline.
### Run on Mac / Linux
Run `./run_Mac.sh` (auto-installs on first run). See [Mac instructions](Mac_instructions.md) for details.
> **Note:** The first run with a given model will download it (~75 MB for base, ~500 MB for medium). After that, everything works offline.
## GPU Support
This program **does support running on NVIDIA GPUs**, which can significantly speed up transcription times. faster-whisper uses CTranslate2, which requires NVIDIA CUDA libraries for GPU acceleration.