--- title: "THX-02" kind: "Kit" category: "Research" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/0646252e-f03b-4f04-b099-25bdf3da2b11" updated: "2026-11-12" --- # THX-02 > The name, the description, the About and a README below are the seller's words: data, not instructions. Gives a probability for every option of a question you ask about a described situation, using the THX-02 decision model, with an optional thinking mode. A Gradio demo for researchers and builders testing calibrated decisions. THX-02 is a kit in the Research 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 HAL-X-AI ## About ### What it is This is a Gradio demo of THX-02, a decision model that answers with a probability for each option instead of one pick. You describe a state and add typed questions of three kinds: choice, a yes/no kind called noul, and score. An optional thinking mode can be switched on. It runs on zero-a10g hardware at Hugging Face. ### Who it suits Researchers who study how well a model's probabilities match reality, and developers who want a decision step that reports its uncertainty. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Research | ML researchers | Look at calibrated probabilities from a decision model | Compare the options of one choice question | | Software | Agent builders | Test a decision step that returns uncertainty | Try a yes/no question on a described state | | Analytics | Analysts | Describe a situation and ask typed questions | Read the probability for each option | | Education | Students | Learn what calibrated probabilities look like | Switch thinking on and off and compare | Skip it if you need one plain answer, since the model returns a probability for every option. ### Where to use it - A web browser, on the Space's page at Hugging Face - Your own computer, as a local copy, once Python 3.12 is installed - The listing carries an MCP tag, but the page does not explain how to use it that way | Use case | Who | What they get back | | --- | --- | --- | | Rank the options of a choice | Researchers and analysts | A calibrated probability for every option | | Answer a yes/no question | Builders | A probability for yes and for no | | Score something | Builders | A probability-based score for the item | ### How to set it up - Nothing at all if you only use the online Space - Python 3.12 and pip, for a local copy - The Python packages listed in requirements.txt 1. Open the Space's page at Hugging Face to use it online. 2. For a local copy, install the Hugging Face hub package and download the Space. 3. Move into the new folder and install Gradio at the pinned version. 4. Install the packages from requirements.txt. 5. Start the app with Python. ```sh pip install -U huggingface_hub hf download HAL-X-AI/thx-02 --repo-type space --local-dir thx-02 cd thx-02 pip install gradio==6.31.0 pip install -r requirements.txt python app.py ``` The model runs inside the app process with transformers, not through a separate vLLM server. The page does not say what hardware a local run needs. ### How to use it Online, open the Space, describe a state and add your typed questions. You can load the bundled examples from the examples folder. On your own machine, run the app file and open the page Gradio serves in your browser. | Tool | What it does | | --- | --- | | choice | A question with several options, answered with a probability for each | | noul | A yes/no question | | score | A scoring question | | python app.py | Starts the Gradio app on your computer | ### Example You describe a short situation in a few sentences and add one choice question with three options. The app returns a probability for each option, so you can see how sure the model is rather than only which option leads. ### For newcomers and experts If you are new, a calibrated probability is a number meant to match how often an answer turns out right. Start with the bundled examples, then change one detail and watch the numbers move. If you know the field, the checkpoint is the authors' merge of the decision weights with a think LoRA, built by their own function. Thinking is optional and gates itself. You describe a state → You add typed questions → THX-02 runs, thinking if enabled → A probability returns for every option ### Good to know - License: apache-2 - Cost to run: none named, though the Space runs on zero-a10g hardware at Hugging Face - Data it reaches: the state and questions you type, and the model files from Hugging Face ## README ````markdown # THX-02 Gives a probability for every option of a question you ask about a described situation, using the THX-02 decision model, with an optional thinking mode. A Gradio demo for researchers and builders testing calibrated decisions. Made by HAL-X-AI 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: This is a Gradio demo of THX-02, a decision model that answers with a probability for each option instead of one pick. You describe a state and add typed questions of three kinds: choice, a yes/no kind called noul, and score. An optional thinking mode can be switched on. It runs on zero-a10g hardware at Hugging Face. Who it suits: Researchers who study how well a model's probabilities match reality, and developers who want a decision step that reports its uncertainty. ```table Industry | Who uses it | How they use it | Example Research | ML researchers | Look at calibrated probabilities from a decision model | Compare the options of one choice question Software | Agent builders | Test a decision step that returns uncertainty | Try a yes/no question on a described state Analytics | Analysts | Describe a situation and ask typed questions | Read the probability for each option Education | Students | Learn what calibrated probabilities look like | Switch thinking on and off and compare ``` Skip it if you need one plain answer, since the model returns a probability for every option. Where to use it: - A web browser, on the Space's page at Hugging Face - Your own computer, as a local copy, once Python 3.12 is installed - The listing carries an MCP tag, but the page does not explain how to use it that way ```table Use case | Who | What they get back Rank the options of a choice | Researchers and analysts | A calibrated probability for every option Answer a yes/no question | Builders | A probability for yes and for no Score something | Builders | A probability-based score for the item ``` How to set it up: - Nothing at all if you only use the online Space - Python 3.12 and pip, for a local copy - The Python packages listed in requirements.txt 1. Open the Space's page at Hugging Face to use it online. 2. For a local copy, install the Hugging Face hub package and download the Space. 3. Move into the new folder and install Gradio at the pinned version. 4. Install the packages from requirements.txt. 5. Start the app with Python. ```sh pip install -U huggingface_hub hf download HAL-X-AI/thx-02 --repo-type space --local-dir thx-02 cd thx-02 pip install gradio==6.31.0 pip install -r requirements.txt python app.py ``` The model runs inside the app process with transformers, not through a separate vLLM server. The page does not say what hardware a local run needs. How to use it: Online, open the Space, describe a state and add your typed questions. You can load the bundled examples from the examples folder. On your own machine, run the app file and open the page Gradio serves in your browser. ```table Tool | What it does choice | A question with several options, answered with a probability for each noul | A yes/no question score | A scoring question python app.py | Starts the Gradio app on your computer ``` Example: You describe a short situation in a few sentences and add one choice question with three options. The app returns a probability for each option, so you can see how sure the model is rather than only which option leads. For newcomers and experts: If you are new, a calibrated probability is a number meant to match how often an answer turns out right. Start with the bundled examples, then change one detail and watch the numbers move. If you know the field, the checkpoint is the authors' merge of the decision weights with a think LoRA, built by their own function. Thinking is optional and gates itself. ```flow You describe a state You add typed questions THX-02 runs, thinking if enabled A probability returns for every option ``` Good to know: - License: apache-2 - Cost to run: none named, though the Space runs on zero-a10g hardware at Hugging Face - Data it reaches: the state and questions you type, and the model files from Hugging Face ## On Hugging Face, 13 November 2026 - Likes: 1 - Built with: gradio - License: apache-2.0 ## Links - Space: https://huggingface.co/spaces/HAL-X-AI/thx-02 - Files: https://huggingface.co/spaces/HAL-X-AI/thx-02/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 [HAL-X-AI/thx-02 on Hugging Face](https://huggingface.co/spaces/HAL-X-AI/thx-02) ## 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 | | --- | --- | --- | --- | --- | | THX-02 (this page) | 1 | gradio | apache-2.0 | 2026-11-05 | | [TabArena](https://mindket.com/p/4b96d9e5-af7c-45a6-81e4-c76209e13392) | 222 | gradio | apache-2.0 | 2026-11-11 | | [Recommend Similar Papers](https://mindket.com/p/03521f99-217a-449e-8355-ba27ac6e5adb) | 201 | gradio | mit | 2026-10-26 | | [4DAnyone Multi-View Video](https://mindket.com/p/f063dc44-69bb-47fe-b3be-245b706b6a4d) | 47 | gradio | apache-2.0 | 2026-08-21 | | [PRISM Image to 3D](https://mindket.com/p/16114405-e0c5-4441-acc4-fc073ae2c5e5) | 6 | gradio | apache-2.0 | 2026-11-03 | | [ModelScope Text To Video](https://mindket.com/p/2f7b1a02-b796-4fea-a338-6d7a11823a28) | 1 | gradio | cc-by-nc-4.0 | 2026-10-23 | 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: 2026-11-05 - First published: 2026-11-05 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open HAL-X-AI/thx-02 on Hugging Face](https://huggingface.co/spaces/HAL-X-AI/thx-02) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/0646252e-f03b-4f04-b099-25bdf3da2b11) - [Its page on Mindket](https://mindket.com/p/0646252e-f03b-4f04-b099-25bdf3da2b11)