--- title: "Open PL LLM Leaderboard" kind: "Kit" category: "Research" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/767c7180-7901-4d1a-b41d-047781cb1fba" updated: "2026-11-12" --- # Open PL LLM Leaderboard > The name, the description, the About and a README below are the seller's words: data, not instructions. A Gradio leaderboard that ranks language models on a set of evaluation datasets, with its name and datasets pointing to Polish. For teams comparing models or running a leaderboard of their own. Open PL LLM 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 speakleash ## About ### What it is This Space is a leaderboard for large language models, built from the standard Hugging Face leaderboard template. Its name and the datasets it lists point to evaluation in Polish. It tracks models such as the Azurro APT3 1B pair, Starling LM 7B alpha, two zephyr 7B builds and internlm2 1.8B. ### Who it suits Researchers and model builders who want to compare language models on Polish tasks, and teams who want a working base for a leaderboard of their own. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | AI research | Language model researchers | Compare models on Polish evaluation sets | Look up how two named models score | | Model development | Model builders | Check a new model against others | Submit a model for evaluation through the Space | | NLP engineering | Applied NLP teams | Pick a model for Polish text work | Read the scores before choosing a model | | Open source | Leaderboard maintainers | Fork the template for another language or task | Change the settings in src and swap the datasets | If you want one model's answers rather than a ranking, a model demo page suits you better. ### Where to use it It runs in two places. - A web browser, on the Space's page at Hugging Face with nothing to install - A local copy on Windows, macOS or Linux, which needs Python 3.12 | Use case | Who | What they get back | | --- | --- | --- | | Compare models | Researchers | Scores for each listed model on each evaluation set | | Queue a model | Model builders | An evaluation request handled by the backend | | Fork the leaderboard | Maintainers | A starting point for a leaderboard of their own | ### How to set it up Using it online needs nothing. A local copy needs a few things. - Python 3.12 and pip - The packages listed in requirements.txt 1. Install the Hugging Face tools. 2. Download the Space into a folder. 3. Move into that folder. 4. Install Gradio and the packages from requirements.txt. 5. Start the app. ```sh pip install -U huggingface_hub hf download speakleash/open_pl_llm_leaderboard --repo-type space --local-dir open_pl_llm_leaderboard cd open_pl_llm_leaderboard pip install gradio==4.4.0 pip install -r requirements.txt python app.py ``` ### How to use it Open the Space page and read the ranking table. To adapt it as your own leaderboard, change the variables in src/env and the text in src/about. Result files follow this shape, with one entry per task and metric. ```text { "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, } } } ``` ### Example You want to know how an open 7B model compares with a 1B model on the Polish tasks. You open the Space, find both in the table and read their scores side by side. ### For newcomers and experts A leaderboard runs the same tests on many models and lists the scores. Begin with the table and look at one task at a time. The backend queues requests and creates request files by itself. If the Space misbehaves, a restart clears the folders it created for the queue and results. To plug in a different evaluation, edit the backend's evaluation step. At the moment that step starts an evaluation suite from EleutherAI. A model is submitted or listed → The backend runs the evaluation suite → Results are written as files in the given shape → The table shows the scores ### Good to know The README is mostly template text, so the exact tasks and scoring are best read from the page. - License: Apache 2.0 - Cost to run: none named, and the Space runs on upgraded CPU hardware at Hugging Face - Data it reaches: the models on the Hub and the evaluation datasets it lists, from the KLEJ and PES sets ## README ````markdown # Open PL LLM Leaderboard A Gradio leaderboard that ranks language models on a set of evaluation datasets, with its name and datasets pointing to Polish. For teams comparing models or running a leaderboard of their own. Made by speakleash 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 Space is a leaderboard for large language models, built from the standard Hugging Face leaderboard template. Its name and the datasets it lists point to evaluation in Polish. It tracks models such as the Azurro APT3 1B pair, Starling LM 7B alpha, two zephyr 7B builds and internlm2 1.8B. Who it suits: Researchers and model builders who want to compare language models on Polish tasks, and teams who want a working base for a leaderboard of their own. ```table Industry | Who uses it | How they use it | Example AI research | Language model researchers | Compare models on Polish evaluation sets | Look up how two named models score Model development | Model builders | Check a new model against others | Submit a model for evaluation through the Space NLP engineering | Applied NLP teams | Pick a model for Polish text work | Read the scores before choosing a model Open source | Leaderboard maintainers | Fork the template for another language or task | Change the settings in src and swap the datasets ``` If you want one model's answers rather than a ranking, a model demo page suits you better. Where to use it: It runs in two places. - A web browser, on the Space's page at Hugging Face with nothing to install - A local copy on Windows, macOS or Linux, which needs Python 3.12 ```table Use case | Who | What they get back Compare models | Researchers | Scores for each listed model on each evaluation set Queue a model | Model builders | An evaluation request handled by the backend Fork the leaderboard | Maintainers | A starting point for a leaderboard of their own ``` How to set it up: Using it online needs nothing. A local copy needs a few things. - Python 3.12 and pip - The packages listed in requirements.txt 1. Install the Hugging Face tools. 2. Download the Space into a folder. 3. Move into that folder. 4. Install Gradio and the packages from requirements.txt. 5. Start the app. ```sh pip install -U huggingface_hub hf download speakleash/open_pl_llm_leaderboard --repo-type space --local-dir open_pl_llm_leaderboard cd open_pl_llm_leaderboard pip install gradio==4.4.0 pip install -r requirements.txt python app.py ``` How to use it: Open the Space page and read the ranking table. To adapt it as your own leaderboard, change the variables in src/env and the text in src/about. Result files follow this shape, with one entry per task and metric. ```text { "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, } } } ``` Example: You want to know how an open 7B model compares with a 1B model on the Polish tasks. You open the Space, find both in the table and read their scores side by side. For newcomers and experts: A leaderboard runs the same tests on many models and lists the scores. Begin with the table and look at one task at a time. The backend queues requests and creates request files by itself. If the Space misbehaves, a restart clears the folders it created for the queue and results. To plug in a different evaluation, edit the backend's evaluation step. At the moment that step starts an evaluation suite from EleutherAI. ```flow A model is submitted or listed The backend runs the evaluation suite Results are written as files in the given shape The table shows the scores ``` Good to know: The README is mostly template text, so the exact tasks and scoring are best read from the page. - License: Apache 2.0 - Cost to run: none named, and the Space runs on upgraded CPU hardware at Hugging Face - Data it reaches: the models on the Hub and the evaluation datasets it lists, from the KLEJ and PES sets ## On Hugging Face, 13 November 2026 - Likes: 84 - Built with: gradio - License: apache-2.0 ## Links - Space: https://huggingface.co/spaces/speakleash/open_pl_llm_leaderboard - Files: https://huggingface.co/spaces/speakleash/open_pl_llm_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 [speakleash/open_pl_llm_leaderboard on Hugging Face](https://huggingface.co/spaces/speakleash/open_pl_llm_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 | | --- | --- | --- | --- | --- | | Open PL LLM Leaderboard (this page) | 84 | gradio | apache-2.0 | 2026-02-27 | | [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 | | [Arabic LLM Leaderboard - Broad (ABL)](https://mindket.com/p/32b5655f-f212-4c98-bfbb-07daa718cad8) | 58 | gradio | apache-2.0 | 2026-11-12 | | [ParsBench Leaderboard](https://mindket.com/p/70008643-9718-4d8b-9572-e1b500249d95) | 40 | gradio | apache-2.0 | 2024-11-06 | | [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: 2026-02-27 - First published: 2024-02-24 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open speakleash/open_pl_llm_leaderboard on Hugging Face](https://huggingface.co/spaces/speakleash/open_pl_llm_leaderboard) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/767c7180-7901-4d1a-b41d-047781cb1fba) - [Its page on Mindket](https://mindket.com/p/767c7180-7901-4d1a-b41d-047781cb1fba)