| --- |
| title: Jevásio |
| emoji: ⚖️ |
| colorFrom: green |
| colorTo: red |
| sdk: gradio |
| sdk_version: 6.28.0 |
| python_version: "3.12" |
| app_file: app.py |
| short_description: Typed decisions for European Portuguese text |
| startup_duration_timeout: 1h |
| license: cc-by-nc-sa-4.0 |
| models: |
| - TigreGotico/jevasio-0.8b |
| - TigreGotico/jevasio-0.8b-v2 |
| - TigreGotico/jevasio-4b |
| - TigreGotico/jevasio-4b-v2 |
| - Qwen/Qwen3.5-0.8B-Base |
| - Qwen/Qwen3.5-4B-Base |
| datasets: |
| - TigreGotico/jevasio-decisions |
| - TigreGotico/jevasio-decisions-v2 |
| tags: |
| - decision-model |
| - european-portuguese |
| - pt-pt |
| --- |
| |
| # Jevásio |
|
|
| Jevásio is a decision model for European Portuguese (pt-PT). It reads a state, which is a text or a JSON object, and a |
| set of typed questions about it. It returns a probability for each option of each question in one forward pass. It |
| does not generate text. |
|
|
| This Space runs four models on ZeroGPU, in bf16. Pick one with the model selector. The 4B models are more accurate, and |
| the 0.8B models are smaller. |
|
|
| - [Jevásio-4B-V2](https://huggingface.co/TigreGotico/jevasio-4b-v2) and |
| [Jevásio-0.8B-V2](https://huggingface.co/TigreGotico/jevasio-0.8b-v2), trained further on more tasks: the language |
| variety of a text, voice commands, news sections, legal areas, sentence relations, offensive language, puns, and |
| translations or summaries with one fact changed. The examples marked (V2) are from those tasks. |
| - [Jevásio-4B](https://huggingface.co/TigreGotico/jevasio-4b) and |
| [Jevásio-0.8B](https://huggingface.co/TigreGotico/jevasio-0.8b), the first versions. |
|
|
| Jevásio-4B and Jevásio-0.8B are [Kev](https://github.com/jaredpalmer/kev) fine-tuned on the |
| [TigreGotico/jevasio-decisions](https://huggingface.co/datasets/TigreGotico/jevasio-decisions) dataset. The V2 models |
| continue from them on |
| [TigreGotico/jevasio-decisions-v2](https://huggingface.co/datasets/TigreGotico/jevasio-decisions-v2). |
|
|
| ## Request shape |
|
|
| A request follows Kev's System One format (`POST /v1/systemone`). Keys are English: the state's field names, the |
| question ids and the option names. Values are Portuguese. |
|
|
| ```json |
| { |
| "state": {"request": "Fui cobrado duas vezes pela encomenda 1182."}, |
| "questions": { |
| "team": {"type": "choice", "instructions": "Que equipa deve tratar deste pedido?", |
| "criteria": {"billing": "Cobranças e reembolsos", "shipping": "Entregas", "returns": "Trocas"}}, |
| "urgent": {"type": "noul", "instructions": "Este pedido precisa de resposta hoje?"}, |
| "frustration": {"type": "score", "instructions": "Quão frustrado está o cliente?", |
| "criteria": ["Calmo", "Incomodado", "Muito zangado"]} |
| } |
| } |
| ``` |
|
|
| There are three question types. A `choice` question picks one of its named options, and each option can have a |
| description. A `noul` question is yes or no, and the answer is p(yes). A `score` question picks a level on an ordered |
| list, and the answer is the expected level. |
|
|
| The **Perguntas** tab builds a request from a form. The **Avançado** tab takes a raw JSON request and shows the raw |
| JSON answer. The same two functions are on the Gradio API as `/decide` and `/systemone`. |
|
|
| ## How it runs |
|
|
| The Space installs Kev from GitHub at commit `1f04cfa28e6a708485b28a9585010b9e436b776e` and loads the model with |
| Kev's own loader, as `python -m kev.serve --run TigreGotico/jevasio-0.8b` does. The probabilities use the calibration |
| temperature stored in the model's `head.pt`. |
|
|
| ## Licence and limits |
|
|
| The models and the dataset are under CC BY-NC-SA 4.0, for non-commercial research only. The model cards list the |
| measured accuracy, the calibration error and the known limits. Do not use the model for decisions with legal, medical, |
| financial or employment consequences without human review. |
|
|
