--- title: "Storytelling" kind: "Kit" category: "Writing" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/bd130b4a-fd63-4f37-803e-f79133a3e639" updated: "2026-11-13" --- # Storytelling > The name, the description, the About and a README below are the seller's words: data, not instructions. Generates stories with GPT-2 in a Streamlit page and uses an emotion classifier model alongside it. For writers, students and developers exploring emotion-aware text generation. Storytelling is a kit in the Writing category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-13. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by jitesh ## About ### What it is Storytelling is a Streamlit app that, by its name, generates stories. The record names two models, GPT-2 for text generation and an English emotion classifier built on DistilRoBERTa. The repository has source and data folders, a setup file and a run script. ### Who it suits It suits writers who want machine-made story drafts, students of text generation, and developers who want a small project with source folders to read. The record does not say how the emotion model is used, so open the page to see. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Writing | Hobby writers | Get a story draft to edit | Start a story and read how it continues | | Education | NLP students | See a text generator paired with an emotion model | Read the src folder to see how they connect | | Software | Python developers | Study a Streamlit project with data and source folders | Open app.py, setup.py and run.sh | You can skip it if you need finished prose with no editing. ### Where to use it - A web browser, on the Space's page on Hugging Face - Windows, macOS or Linux with Python, from a downloaded copy | Use case | Who | What they get back | | --- | --- | --- | | Draft a short story | Writers | Text from the GPT-2 model | | Study emotion and generation | Students | A project that combines two models | | Reuse as a base | Developers | A Streamlit project with data and source folders | ### How to set it up - Nothing at all if you use the online Space - Python on your computer, only if you run a copy - The packages listed in requirements.txt 1. Open the Space's page in a browser to use it with nothing to install. 2. To run a copy, install the Hugging Face Hub package and download the Space. 3. Move into the new folder, then install Streamlit and the listed requirements. 4. Start the app with Streamlit. ```sh pip install -U huggingface_hub hf download jitesh/storytelling --repo-type space --local-dir storytelling cd storytelling pip install streamlit pip install -r requirements.txt streamlit run app.py ``` ### How to use it Online, open the Space and use the controls on its page. On your own machine, run the main file with Streamlit from the Space folder, then use the page it serves. The record does not list the controls, so look at the page. ```sh streamlit run app.py ``` ### Example You open the Space and give it the start of a story. The app continues it with GPT-2 and may use the emotion model in the process. The record shows no sample, so check the page for the exact inputs. ### For newcomers and experts A text generator continues what you give it, one word piece at a time. Start by opening the Space, typing a short story opening and reading what comes back. If you know the field, GPT-2 is a small older language model, so output can drift and repeat. The emotion model labels text by feeling, which hints at a way to steer or check the mood. The record gives no details on how, so read the src folder. You enter a story opening → GPT-2 continues the text → The emotion model labels the feeling of the text → The page shows the story ### Good to know - License: MIT, as listed on the Space - Cost to run: none named - Data it reaches: the text you enter, the two models it names and the files in its data folder - Not for: the record names no exclusions, so read generated text before you share it ## README ````markdown # Storytelling Generates stories with GPT-2 in a Streamlit page and uses an emotion classifier model alongside it. For writers, students and developers exploring emotion-aware text generation. Made by jitesh 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: Storytelling is a Streamlit app that, by its name, generates stories. The record names two models, GPT-2 for text generation and an English emotion classifier built on DistilRoBERTa. The repository has source and data folders, a setup file and a run script. Who it suits: It suits writers who want machine-made story drafts, students of text generation, and developers who want a small project with source folders to read. The record does not say how the emotion model is used, so open the page to see. ```table Industry | Who uses it | How they use it | Example Writing | Hobby writers | Get a story draft to edit | Start a story and read how it continues Education | NLP students | See a text generator paired with an emotion model | Read the src folder to see how they connect Software | Python developers | Study a Streamlit project with data and source folders | Open app.py, setup.py and run.sh ``` You can skip it if you need finished prose with no editing. Where to use it: - A web browser, on the Space's page on Hugging Face - Windows, macOS or Linux with Python, from a downloaded copy ```table Use case | Who | What they get back Draft a short story | Writers | Text from the GPT-2 model Study emotion and generation | Students | A project that combines two models Reuse as a base | Developers | A Streamlit project with data and source folders ``` How to set it up: - Nothing at all if you use the online Space - Python on your computer, only if you run a copy - The packages listed in requirements.txt 1. Open the Space's page in a browser to use it with nothing to install. 2. To run a copy, install the Hugging Face Hub package and download the Space. 3. Move into the new folder, then install Streamlit and the listed requirements. 4. Start the app with Streamlit. ```sh pip install -U huggingface_hub hf download jitesh/storytelling --repo-type space --local-dir storytelling cd storytelling pip install streamlit pip install -r requirements.txt streamlit run app.py ``` How to use it: Online, open the Space and use the controls on its page. On your own machine, run the main file with Streamlit from the Space folder, then use the page it serves. The record does not list the controls, so look at the page. ```sh streamlit run app.py ``` Example: You open the Space and give it the start of a story. The app continues it with GPT-2 and may use the emotion model in the process. The record shows no sample, so check the page for the exact inputs. For newcomers and experts: A text generator continues what you give it, one word piece at a time. Start by opening the Space, typing a short story opening and reading what comes back. If you know the field, GPT-2 is a small older language model, so output can drift and repeat. The emotion model labels text by feeling, which hints at a way to steer or check the mood. The record gives no details on how, so read the src folder. ```flow You enter a story opening GPT-2 continues the text The emotion model labels the feeling of the text The page shows the story ``` Good to know: - License: MIT, as listed on the Space - Cost to run: none named - Data it reaches: the text you enter, the two models it names and the files in its data folder - Not for: the record names no exclusions, so read generated text before you share it ## On Hugging Face, 13 November 2026 - Likes: 1 - Built with: streamlit - License: mit ## Links - Space: https://huggingface.co/spaces/jitesh/storytelling - Files: https://huggingface.co/spaces/jitesh/storytelling/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 [jitesh/storytelling on Hugging Face](https://huggingface.co/spaces/jitesh/storytelling) ## 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 | | --- | --- | --- | --- | --- | | Storytelling (this page) | 1 | streamlit | mit | 2022-03-21 | | [Streamlit Machine Translate](https://mindket.com/p/c05de44c-4627-497b-8f06-e3af256b2c05) | 16 | streamlit | gpl-3.0 | 2026-08-08 | | [Gpt2 Home](https://mindket.com/p/92ece401-08e5-4bc1-bc86-5a7bc0782c19) | 4 | streamlit | apache-2.0 | 2023-10-15 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## 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: 2022-03-21 - First published: 2022-03-02 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open jitesh/storytelling on Hugging Face](https://huggingface.co/spaces/jitesh/storytelling) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/bd130b4a-fd63-4f37-803e-f79133a3e639) - [Its page on Mindket](https://mindket.com/p/bd130b4a-fd63-4f37-803e-f79133a3e639)