--- title: "ParsBench Leaderboard" kind: "Kit" category: "Research" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/70008643-9718-4d8b-9572-e1b500249d95" updated: "2026-11-12" --- # ParsBench Leaderboard > The name, the description, the About and a README below are the seller's words: data, not instructions. A leaderboard from ParsBench that scores models on Persian language datasets, with the code to run or adapt your own copy. For Persian NLP researchers and engineers comparing models. ParsBench Leaderboard 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 ParsBench ## About ### What it is This Leaderboard is a results page from ParsBench. Going by the datasets it names, it scores models on Persian language tasks. Those datasets include pn\_summary, the ParsiNLU sets for entailment, reading comprehension and translation in both directions, and khayyam-challenge. The repository also holds the code that builds the board. ### Who it suits It suits people who work with Persian text and want measured scores before they pick a model. Who might use this leaderboard | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Persian language technology | Researchers | Compare models on shared Persian datasets | Look up how a model scores on a named dataset | | AI engineering | Engineers | Shortlist a model for a Persian feature | Compare two candidates on the task closest to theirs | | Leaderboard hosting | Maintainers | Adapt the code to run a leaderboard of their own | Change the tasks in src/about.py | If you only work in other languages, you can skip it. ### Where to use it You can read it online or run a copy yourself. - Web browser: the Space's page on Hugging Face, with nothing to install - Windows, macOS or Linux: a local copy that runs with Python - Hugging Face Spaces: where the hosted board runs, on the cpu-basic hardware tier What the leaderboard is good for | Use case | Who | What they get back | | --- | --- | --- | | Compare models on Persian tasks | Engineers | Scores for each model across the named datasets | | Study one task | Researchers | Results for a single dataset such as a translation pair | | Run your own leaderboard | Maintainers | A local copy to adapt, fed by results saved as JSON files | ### How to set it up The hosted board needs nothing. A local copy needs Python and pip. - Python, with pip - The Python packages that requirements.txt lists 1. Install the huggingface\_hub package. 2. Download the Space's files into a folder. 3. Move into that folder. 4. Install Gradio 5.5.0. 5. Install the packages from requirements.txt. 6. Start the app with Python. ```sh pip install -U huggingface_hub hf download ParsBench/leaderboard --repo-type space --local-dir leaderboard cd leaderboard pip install gradio==5.5.0 pip install -r requirements.txt python app.py ``` To point a copy at your own leaderboard, change the path in src/env.py and the tasks in src/about.py. ### How to use it Open the Space online, or start your copy with the command below. Then read the leaderboard table and compare the models you care about. ```sh python app.py ``` Results go in as JSON files with a config part and a results part, in this shape. ```json { "config": { "model_dtype": "torch.float16", # or torch.bfloat16 or 8bit or 4bit "model_name": "path of the model on the hub: org/model", "model_sha": "revision on the hub", }, "results": { "task_name": { "metric_name": score, }, "task_name2": { "metric_name": score, } } } ``` The files that shape the board | Tool | What it does | | --- | --- | | src/env.py | Holds most of the variables you change, such as the leaderboard path | | src/about.py | Holds the tasks | | src/display/utils.py | Defines the main table's column names and properties | | src/leaderboard/read\_evals.py | Reads results and request files and turns them into table rows | | src/submission/submit.py | Decides which submissions are allowed or filtered | ### Example You need a model for Persian summaries. You open the leaderboard, look at the scores on the pn\_summary dataset, and compare the models that rank near the top there. ### For newcomers and experts If you are new to this, open the Space and look at the main table before you change anything. Pick two models and compare their scores. If you know the field, results are plain JSON with a config block that records the model's dtype, name and revision, and a results block of task and metric scores. The code reads those files, along with request files it creates itself, and turns them into dataframe rows. Submission checks live in src/submission/check\_validity.py. Results and request files are stored → The app reads and converts them → They become rows in the main table → You compare models on the board ### Good to know The board creates some folders of its own while it runs. - Created folders: the app makes four working folders for queues and results, plus backups, and restarting the Space clears them if something goes wrong - Requests: request files are made automatically by the tool - Hosting: the hosted copy runs on cpu-basic hardware - License: apache-2 - Cost to run: none named - Data it reaches: the results and request files it reads, plus the Python packages pip installs from requirements.txt ## README ````markdown # ParsBench Leaderboard A leaderboard from ParsBench that scores models on Persian language datasets, with the code to run or adapt your own copy. For Persian NLP researchers and engineers comparing models. Made by ParsBench 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 Leaderboard is a results page from ParsBench. Going by the datasets it names, it scores models on Persian language tasks. Those datasets include pn_summary, the ParsiNLU sets for entailment, reading comprehension and translation in both directions, and khayyam-challenge. The repository also holds the code that builds the board. Who it suits: It suits people who work with Persian text and want measured scores before they pick a model. ```table Title: Who might use this leaderboard Industry | Who uses it | How they use it | Example Persian language technology | Researchers | Compare models on shared Persian datasets | Look up how a model scores on a named dataset AI engineering | Engineers | Shortlist a model for a Persian feature | Compare two candidates on the task closest to theirs Leaderboard hosting | Maintainers | Adapt the code to run a leaderboard of their own | Change the tasks in src/about.py ``` If you only work in other languages, you can skip it. Where to use it: You can read it online or run a copy yourself. - Web browser: the Space's page on Hugging Face, with nothing to install - Windows, macOS or Linux: a local copy that runs with Python - Hugging Face Spaces: where the hosted board runs, on the cpu-basic hardware tier ```table Title: What the leaderboard is good for Use case | Who | What they get back Compare models on Persian tasks | Engineers | Scores for each model across the named datasets Study one task | Researchers | Results for a single dataset such as a translation pair Run your own leaderboard | Maintainers | A local copy to adapt, fed by results saved as JSON files ``` How to set it up: The hosted board needs nothing. A local copy needs Python and pip. - Python, with pip - The Python packages that requirements.txt lists 1. Install the huggingface_hub package. 2. Download the Space's files into a folder. 3. Move into that folder. 4. Install Gradio 5.5.0. 5. Install the packages from requirements.txt. 6. Start the app with Python. ```sh pip install -U huggingface_hub hf download ParsBench/leaderboard --repo-type space --local-dir leaderboard cd leaderboard pip install gradio==5.5.0 pip install -r requirements.txt python app.py ``` To point a copy at your own leaderboard, change the path in src/env.py and the tasks in src/about.py. How to use it: Open the Space online, or start your copy with the command below. Then read the leaderboard table and compare the models you care about. ```sh python app.py ``` Results go in as JSON files with a config part and a results part, in this shape. ```json { "config": { "model_dtype": "torch.float16", # or torch.bfloat16 or 8bit or 4bit "model_name": "path of the model on the hub: org/model", "model_sha": "revision on the hub", }, "results": { "task_name": { "metric_name": score, }, "task_name2": { "metric_name": score, } } } ``` ```table Title: The files that shape the board Tool | What it does src/env.py | Holds most of the variables you change, such as the leaderboard path src/about.py | Holds the tasks src/display/utils.py | Defines the main table's column names and properties src/leaderboard/read_evals.py | Reads results and request files and turns them into table rows src/submission/submit.py | Decides which submissions are allowed or filtered ``` Example: You need a model for Persian summaries. You open the leaderboard, look at the scores on the pn_summary dataset, and compare the models that rank near the top there. For newcomers and experts: If you are new to this, open the Space and look at the main table before you change anything. Pick two models and compare their scores. If you know the field, results are plain JSON with a config block that records the model's dtype, name and revision, and a results block of task and metric scores. The code reads those files, along with request files it creates itself, and turns them into dataframe rows. Submission checks live in src/submission/check_validity.py. ```flow Results and request files are stored The app reads and converts them They become rows in the main table You compare models on the board ``` Good to know: The board creates some folders of its own while it runs. - Created folders: the app makes four working folders for queues and results, plus backups, and restarting the Space clears them if something goes wrong - Requests: request files are made automatically by the tool - Hosting: the hosted copy runs on cpu-basic hardware - License: apache-2 - Cost to run: none named - Data it reaches: the results and request files it reads, plus the Python packages pip installs from requirements.txt ## On Hugging Face, 13 November 2026 - Likes: 40 - Built with: gradio - License: apache-2.0 ## Links - Space: https://huggingface.co/spaces/ParsBench/leaderboard - Files: https://huggingface.co/spaces/ParsBench/leaderboard/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, 5 KB, downloaded as a zip. ```text README.md 5 KB ``` ## Source [ParsBench/leaderboard on Hugging Face](https://huggingface.co/spaces/ParsBench/leaderboard) ## 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 | | --- | --- | --- | --- | --- | | ParsBench Leaderboard (this page) | 40 | gradio | apache-2.0 | 2024-11-06 | | [Open VLM Leaderboard](https://mindket.com/p/9382a913-7563-4967-88b1-0f2458cb00bc) | 1,034 | gradio | apache-2.0 | 2026-03-11 | | [Open VLM Video Leaderboard](https://mindket.com/p/6cbb4dc8-fd02-4668-a8d1-8e915f3c3d1f) | 136 | gradio | apache-2.0 | 2024-11-21 | | [Open PL LLM Leaderboard](https://mindket.com/p/767c7180-7901-4d1a-b41d-047781cb1fba) | 84 | gradio | apache-2.0 | 2026-02-27 | | [Arabic LLM Leaderboard - Broad (ABL)](https://mindket.com/p/32b5655f-f212-4c98-bfbb-07daa718cad8) | 58 | gradio | apache-2.0 | 2026-11-12 | | [Open Universal Arabic Asr Leaderboard](https://mindket.com/p/f182e681-eb3b-45fc-8e01-10b2888adc54) | 16 | gradio | apache-2.0 | 2026-10-15 | 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: 2024-11-06 - First published: 2024-07-12 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open ParsBench/leaderboard on Hugging Face](https://huggingface.co/spaces/ParsBench/leaderboard) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/70008643-9718-4d8b-9572-e1b500249d95) - [Its page on Mindket](https://mindket.com/p/70008643-9718-4d8b-9572-e1b500249d95)