Update README.md

README.md

@@ -3,8 +3,32 @@ library_name: transformers.js
 base_model: deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
 ---
 
-https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B with ONNX weights to be compatible with Transformers.js.
 
+[<img src="https://cdn-avatars.huggingface.co/v1/production/uploads/67b2f4e49edebc815a3a4739/R1g957j1aBbx8lhZbWmxw.jpeg" width="200"/>](https://huggingface.co/fjmgAI)
+
+## Fine-Tuned Model
+
+**`fjmgAI/b1-R1-1.5B-ONNX`**
+
+## Base Model
+**`deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B`**
+
+## 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.
+Using ONNx runtime to transform the resulting model weights and make it compatible with Transformers.js.
+
+## 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 focus was on retaining the model's **instructional abilities** while improving its **understanding and generation** of Spanish text.
 
 
 ## Usage (Transformers.js)
@@ -98,4 +122,12 @@ x = 1 \quad \text{or} \quad x = 2
 
 ---
 
+## 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
+
+[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)  [<img src="https://camo.githubusercontent.com/9585eb3e70c8138cbc0f73de7e970be4c668e957e45d16fc3ee6687fcc1da905/68747470733a2f2f68756767696e67666163652e636f2f64617461736574732f74726c2d6c69622f646f63756d656e746174696f6e2d696d616765732f7265736f6c76652f6d61696e2f74726c5f62616e6e65725f6461726b2e706e67" width="200"/>](https://github.com/huggingface/trl?tab=readme-ov-file)
+
 Note: Having a separate repo for ONNX weights is intended to be a temporary solution until WebML gains more traction. If you would like to make your models web-ready, we recommend converting to ONNX using [🤗 Optimum](https://huggingface.co/docs/optimum/index) and structuring your repo like this one (with ONNX weights located in a subfolder named `onnx`).