---
base_model: unsloth/qwen2.5-3b-instruct-unsloth-bnb-4bit
tags:
- text-generation-inference
- transformers
- unsloth
- qwen2
- gguf
license: apache-2.0
language:
- en
- es
datasets:
- Kukedlc/dpo-orpo-spanish-15k
library_name: transformers
---
[
](https://huggingface.co/fjmgAI)
## Fine-Tuned Model
**`fjmgAI/b1-R1-Zero-3B-GGUF`**
## Base Model
**`unsloth/qwen2.5-3b-instruct-unsloth-bnb-4bit`**
## Fine-Tuning Method
Fine-tuning was performed using **[`unsloth`](https://github.com/unslothai/unsloth)**, an efficient fine-tuning framework optimized for low-resource environments and Huggingface's TRL library.
## Dataset
**[`Kukedlc/dpo-orpo-spanish-15k`](https://huggingface.co/datasets/Kukedlc/dpo-orpo-spanish-15k)**
### Description
A Spanish-language dataset containing **15,000 examples**, designed for **Direct Preference Optimization (DPO)** or **Outcome-Regularized Preference Optimization (ORPO).**
### Adaptation
The dataset was adapted to a reasoning-based format for GPRO, enhancing its ability to guide preference-based decision-making during fine-tuning. This adaptation ensures better alignment with instruction-following tasks in Spanish.
## Fine-Tuning Details
- The model was trained using the **GPRO algorithm**, leveraging structured preference data to refine its response generation.
- The model was fine-tuned to maintain its **4-bit quantization (`bnb-4bit`)** for memory efficiency while aligning its outputs with the characteristics of the Spanish dataset.
- The focus was on retaining the model's **instructional abilities** while improving its **understanding and generation** of Spanish text.
## Purpose
This fine-tuned model is intended for **Spanish-language applications** that require efficient AI that follows instructions using a **lightweight reasoning process.**
- **Developed by:** fjmgAI
- **License:** apache-2.0
[
](https://github.com/unslothai/unsloth) [
](https://github.com/huggingface/trl?tab=readme-ov-file)