| ---
|
| language:
|
| - en
|
| - pt
|
| tags:
|
| - code
|
| - instruction-tuning
|
| - portuguese
|
| - reasoning
|
| - cosmos-9b
|
| - education
|
| size_categories:
|
| - 100K<n<1M
|
| ---
|
|
|
| # COSMOS 9B Dataset
|
|
|
| ## Dataset Description
|
| This dataset is a meticulously curated mixture of 100,000 high-quality instruction-response pairs designed specifically for fine-tuning the **COSMOS 9B** model. It aims to create an AI model that excels as an educator and coding assistant, with strong reasoning capabilities and fluency in Brazilian Portuguese (PT-BR).
|
|
|
| The dataset includes injected Chain-of-Thought (<think>...</think>) reasoning steps in Portuguese for a subset of the coding and logic prompts, teaching the model to reason in PT-BR before providing the final answer.
|
|
|
| ## Dataset Composition
|
| - **CodeFeedback-Filtered-Instruction (25k):** Advanced programming and logic queries.
|
| - **Magicoder-Evol-Instruct (20k):** Complex, evolved coding trajectories.
|
| - **evol-codealpaca-v1 (20k):** C/C++, Python, and algorithmic problem solving.
|
| - **Magicoder-OSS-Instruct (10k):** Grounded, realistic open-source coding instructions.
|
| - **Pt-Corpus-Instruct (15k):** Deep Brazilian Portuguese conversational fluency.
|
| - **SlimOrca (10k):** Advanced general reasoning and instruction following (crucial for ENEM/Vestibular logic).
|
|
|
| ## Intended Use
|
| This dataset is specifically intended for the Supervised Fine-Tuning (SFT) of the COSMOS 9B V1 base merge model. |
