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Transformers Tutorials

Transformers Tutorials is a public repository of Jupyter notebooks demonstrating Hugging Face Transformers models. The demos are implemented in PyTorch and cover inference, fine-tuning, evaluation and model visualization across language, audio and computer-vision tasks.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Transformers Tutorials — OpenViST project profile in AI Developer Tools & SDKs.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use it when you want a concrete notebook example for a Transformers model or task, rather than a packaged application. Readers new to Hugging Face or Transformers can start with the course recommended in the repository README.

Who it is for

  • Developers exploring hands-on examples of Hugging Face Transformers in PyTorch.
  • Learners seeking model-specific demonstrations for language, audio or computer-vision tasks.

Documented uses

  • Study an example of BERT fine-tuning for named entity recognition or multi-label text classification.
  • Explore audio classification with an Audio Spectrogram Transformer notebook.
  • Review examples of object detection, image segmentation, depth estimation or model attention visualization.
  • Examine notebooks for model inference, custom-dataset fine-tuning or evaluation.
Before you choose

Requirements & limits

The repository is public and identifies the MIT license. The README links selected notebooks to Google Colab.

  • The examples are Jupyter notebooks implemented in PyTorch.
  • The README lists task-specific demonstrations, including BERT text classification, audio classification, DETR object detection and CLIPSeg image segmentation.
  • Some examples are linked for opening in Google Colab; the repository also provides the notebooks as source.
  • The README recommends Hugging Face’s free course for readers unfamiliar with Transformers.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Explore a Hugging Face computer-vision overview notebook

Review the repository’s notebook overview of the Hugging Face computer-vision ecosystem.

Before you start

  • Access to the public Transformers-Tutorials repository.

Steps

  1. Open the repository README.

  2. Follow the link to the Hugging Face vision ecosystem overview notebook.

  3. Use its corresponding video for additional context, if desired.

Expected outcome

You reach the computer-vision ecosystem overview notebook and its associated video.

Guide limitations

  • The README identifies the overview as dating from June 2022.
  • The source does not document notebook execution or environment setup.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
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Sources checked
14 October 2026
Original website title
NielsRogge/Transformers-Tutorials · Official homepage title · retained in its source language
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