--- title: "Image Caption With Vit Gpt2" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/61e0c848-db9c-47f2-a292-b24386584736" updated: "2026-11-12" --- # Image Caption With Vit Gpt2 > The name, the description, the About and a README below are the seller's words: data, not instructions. A Gradio app that writes a short caption for a picture, pairing a vision transformer with a GPT-2 style text model. It suits people who want to try image captioning in a browser. Image Caption With Vit Gpt2 is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-12. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by Amrrs ## About ### What it is Image Caption With Vit Gpt2 is a Gradio app on Hugging Face Spaces that writes a short caption for a picture. It pairs a vision transformer with a GPT-2 style language model, and it names three models, including google/vit-base-patch16-224-in21k and sachin/vit2distilgpt2. The repository also holds one sample photo. ### Who it suits It suits people who want to try automatic image captioning in a browser, and learners who want a short example of an image model feeding a text model. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Accessibility | Content editors | Try a first draft of picture descriptions | Open the Space and give it a photo | | Machine learning | Students | Read app.py to see how an image encoder and a text decoder fit | Download the Space and open app.py | | Education | Instructors | Show image captioning in a web page | Click the sample photo in class | Anyone who needs production-grade captions or measured quality can skip it, since the source gives none. ### Where to use it - A web browser, straight from the Space page on Hugging Face - Windows, macOS or Linux with Python, as a local copy | Use case | Who | What they get back | | --- | --- | --- | | Caption a photo | Anyone curious | A short text description of the picture | | Study an image-to-text demo | Learners | An app file, a requirements file and one sample photo | ### How to set it up Using it online needs nothing. A local copy needs these first. - Python and pip - The huggingface\_hub package, to fetch the files - The packages in requirements.txt, plus Gradio 1. Install the Hugging Face Hub package. 2. Download the Space into a folder called image-caption-with-vit-gpt2. 3. Move into that folder. 4. Install Gradio, then the packages from requirements.txt. 5. Start the app. ```sh pip install -U huggingface_hub hf download Amrrs/image-caption-with-vit-gpt2 --repo-type space --local-dir image-caption-with-vit-gpt2 cd image-caption-with-vit-gpt2 pip install gradio pip install -r requirements.txt python app.py ``` ### How to use it Open the Space page on Hugging Face, give it a picture and read the caption it returns. For a local copy, run python app.py in the folder and open the page it starts. ### Example You upload a photo of a dog on a beach. The app passes it through the vision model and the text model and shows a short sentence describing the picture. ### For newcomers and experts If you are new, click the sample photo on the Space page first. Image captioning means a program looks at a picture and writes a sentence about it. If you know the field, the named checkpoints are a ViT encoder, a vit2distilgpt2 model and a DistilGPT-2 decoder. The source does not give training data or quality figures, so judge the captions on your own images. You give the app a picture → The ViT encoder reads the image → The GPT-2 style decoder writes a caption ### Good to know - Captions are generated by the named models, so check them before you rely on them - It needs Gradio and the packages in requirements.txt - License: mit - Cost to run: none named - Data it reaches: the pictures you give it and the three models it names ## README ````markdown # Image Caption With Vit Gpt2 A Gradio app that writes a short caption for a picture, pairing a vision transformer with a GPT-2 style text model. It suits people who want to try image captioning in a browser. Made by Amrrs on Hugging Face. These notes are Mindket's, written from its Space page and README; the app's own files and license are on Hugging Face. ## About What it is: Image Caption With Vit Gpt2 is a Gradio app on Hugging Face Spaces that writes a short caption for a picture. It pairs a vision transformer with a GPT-2 style language model, and it names three models, including google/vit-base-patch16-224-in21k and sachin/vit2distilgpt2. The repository also holds one sample photo. Who it suits: It suits people who want to try automatic image captioning in a browser, and learners who want a short example of an image model feeding a text model. ```table Industry | Who uses it | How they use it | Example Accessibility | Content editors | Try a first draft of picture descriptions | Open the Space and give it a photo Machine learning | Students | Read app.py to see how an image encoder and a text decoder fit | Download the Space and open app.py Education | Instructors | Show image captioning in a web page | Click the sample photo in class ``` Anyone who needs production-grade captions or measured quality can skip it, since the source gives none. Where to use it: - A web browser, straight from the Space page on Hugging Face - Windows, macOS or Linux with Python, as a local copy ```table Use case | Who | What they get back Caption a photo | Anyone curious | A short text description of the picture Study an image-to-text demo | Learners | An app file, a requirements file and one sample photo ``` How to set it up: Using it online needs nothing. A local copy needs these first. - Python and pip - The huggingface_hub package, to fetch the files - The packages in requirements.txt, plus Gradio 1. Install the Hugging Face Hub package. 2. Download the Space into a folder called image-caption-with-vit-gpt2. 3. Move into that folder. 4. Install Gradio, then the packages from requirements.txt. 5. Start the app. ```sh pip install -U huggingface_hub hf download Amrrs/image-caption-with-vit-gpt2 --repo-type space --local-dir image-caption-with-vit-gpt2 cd image-caption-with-vit-gpt2 pip install gradio pip install -r requirements.txt python app.py ``` How to use it: Open the Space page on Hugging Face, give it a picture and read the caption it returns. For a local copy, run python app.py in the folder and open the page it starts. Example: You upload a photo of a dog on a beach. The app passes it through the vision model and the text model and shows a short sentence describing the picture. For newcomers and experts: If you are new, click the sample photo on the Space page first. Image captioning means a program looks at a picture and writes a sentence about it. If you know the field, the named checkpoints are a ViT encoder, a vit2distilgpt2 model and a DistilGPT-2 decoder. The source does not give training data or quality figures, so judge the captions on your own images. ```flow You give the app a picture The ViT encoder reads the image The GPT-2 style decoder writes a caption ``` Good to know: - Captions are generated by the named models, so check them before you rely on them - It needs Gradio and the packages in requirements.txt - License: mit - Cost to run: none named - Data it reaches: the pictures you give it and the three models it names ## On Hugging Face, 13 November 2026 - Likes: 6 - Built with: gradio - License: mit ## Links - Space: https://huggingface.co/spaces/Amrrs/image-caption-with-vit-gpt2 - Files: https://huggingface.co/spaces/Amrrs/image-caption-with-vit-gpt2/tree/main ## Try it Open the Space in your browser, or copy it to your own Hugging Face account from its page. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 4 KB, downloaded as a zip. ```text README.md 4 KB ``` ## Source [Amrrs/image-caption-with-vit-gpt2 on Hugging Face](https://huggingface.co/spaces/Amrrs/image-caption-with-vit-gpt2) ## Compare with similar Listed Hugging Face Spaces in the same category that share the most tags with this one. | Product | Likes | Built with | License | Last change | | --- | --- | --- | --- | --- | | Image Caption With Vit Gpt2 (this page) | 6 | gradio | mit | 2022-01-29 | | [FLUX.1 dev](https://mindket.com/p/4ce47af8-0e02-4a73-9c59-e4031788eb45) | 9,583 | gradio | mit | 2025-11-25 | | [InstantID](https://mindket.com/p/54fcb36c-756a-4797-80c1-05779f87ebbd) | 3,659 | gradio | apache-2.0 | 2025-08-26 | | [Chat With Janus-Pro-7B](https://mindket.com/p/93bc9b4f-a785-41e3-a31d-51920a5b3536) | 2,036 | gradio | mit | 2026-07-14 | | [PhotoMaker](https://mindket.com/p/b3e336b4-4a67-4e52-8c2e-1e94d392ac71) | 1,960 | gradio | apache-2.0 | 2025-08-28 | | [Z Image Turbo](https://mindket.com/p/adfd87b7-3f3e-405e-95c8-1957bc0da52a) | 1,940 | gradio | apache-2.0 | 2026-05-22 | Numbers as Mindket last read them, on 2026-11-12. ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2022-01-29 - First published: 2022-03-02 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open Amrrs/image-caption-with-vit-gpt2 on Hugging Face](https://huggingface.co/spaces/Amrrs/image-caption-with-vit-gpt2) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/61e0c848-db9c-47f2-a292-b24386584736) - [Its page on Mindket](https://mindket.com/p/61e0c848-db9c-47f2-a292-b24386584736)