# [Accelerate Whisper on Arm with Hugging Face Transformers](https://learn.arm.com/learning-paths/servers-and-cloud-computing/whisper/)

## In this learning path

- [Introduction](https://learn.arm.com/learning-paths/servers-and-cloud-computing/whisper/)
- [Demo](https://learn.arm.com/learning-paths/servers-and-cloud-computing/whisper/_demo/)
- [Set up the Whisper Model](https://learn.arm.com/learning-paths/servers-and-cloud-computing/whisper/whisper/)
- [Run the Whisper Model](https://learn.arm.com/learning-paths/servers-and-cloud-computing/whisper/whisper_deploy/)
- [Next Steps](https://learn.arm.com/learning-paths/servers-and-cloud-computing/whisper/_next-steps/)

## About this Learning Path

| Skill level:  | Introductory           |
|---------------|------------------------|
| Reading time: | 15 min                 |
| Last updated: | 31 Jul 2026            |

| Author:                                   | Nobel Chowdary Mandepudi, Arm          |
|-------------------------------------------|----------------------------------------|
| Arm IP:                                   | [Neoverse](https://support.arm.com/?tab=compute-ip&Product%20Type=Infrastructure%20Processors) |
| Tags:                                     | ML, AWS, Microsoft Azure, Google Cloud, Oracle, Linux, Python, Whisper, Demo, Hugging Face |

### Who is this for?
This Learning Path is for software developers familiar with basic machine learning concepts and looking to run the OpenAI Whisper Automatic Speech Recognition (ASR) model efficiently, using an Arm-based cloud instance.

### What will you learn?
Upon completion of this Learning Path, you will be able to:
- Install the dependencies for the Whisper ASR Model.
- Run the Whisper model using Hugging Face Transformers.
- Enable performance-enhancing features for running the model on Arm CPUs.
- Evaluate transcript generation times using Whisper.

### Prerequisites
Before starting, you will need the following:
- An [Arm-based compute instance](https://learn.arm.com/learning-paths/servers-and-cloud-computing/intro/) running Ubuntu with 32 cores, 8GB of RAM, and 32GB of disk space.
- Basic knowledge of Python.
- Familiarity with machine learning concepts.
- Familiarity with the fundamentals of the Whisper ASR Model.