Update README.md

README.md

@@ -1,22 +1,69 @@
 ---
 base_model: unsloth/Qwen3-0.6B-unsloth-bnb-4bit
 tags:
+- text-generation
 - text-generation-inference
 - transformers
 - unsloth
 - qwen3
 - gguf
+- math
+- enosis-labs
+- math-mini
 license: apache-2.0
 language:
 - en
+library_name: llama.cpp # O la principal librería para GGUF que recomiendes
+pipeline_tag: text-generation
 ---
 
-# Uploaded  model
+# Math Mini 0.6B (Preview) - GGUF
 
-- **Developed by:** enosislabs
-- **License:** apache-2.0
-- **Finetuned from model :** unsloth/Qwen3-0.6B-unsloth-bnb-4bit
+## Model Card for `enosislabs/math-mini-0.6B-preview-gguf`
 
-This qwen3 model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
+<p align="center">
+  <img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="170"/>
+</p>
 
-[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
+**Math Mini 0.6B (Preview)** is a specialized language model developed by **Enosis Labs**, fine-tuned for mathematical problem-solving. This compact 0.6 billion parameter model is part of our "Math Mini" series, designed for efficiency and accessibility, particularly for performing mathematical reasoning tasks.
+
+This GGUF version is quantized and optimized for running locally on CPUs and other supported hardware through interfaces like `llama.cpp`, `LM Studio`, `Oobabooga Text Generation WebUI`, etc.
+
+**Please note: This is a preview version.** We are actively working on improvements and further evaluations.
+
+## Model Details
+
+* **Developed by:** [Enosis Labs](https://huggingface.co/enosislabs) (¡Asegúrate de que este enlace sea correcto o créalo!)
+* **Model type:** Qwen3-based Decoder-only Transformer
+* **Series:** Math Mini
+* **Version:** 0.6B (Preview)
+* **Language(s):** Primarily English (enfocado en problemas matemáticos en inglés)
+* **License:** Apache 2.0
+* **Finetuned from:** `unsloth/Qwen3-0.6B-unsloth-bnb-4bit`
+* **Fine-tuning Frameworks:** [Unsloth](https://github.com/unslothai/unsloth) for 2x faster training and optimized memory usage, in conjunction with Hugging Face's [TRL](https://github.com/huggingface/trl) library.
+* **Fine-tuning Data:** Fine-tuned on a curated collection of mathematical reasoning datasets, including algebraic problems, multi-step arithmetic, and word problems. Key datasets included variants of AQuA-RAT and OpenMathReasoning.
+
+## Intended Uses
+
+This model is intended for (but not limited to):
+
+* Assisting with grade-school to early high-school level mathematical problems.
+* Solving algebraic equations and multi-step arithmetic.
+* Understanding and processing mathematical questions posed in natural language.
+* Use as a lightweight math reasoning engine in applications where resource efficiency is crucial.
+* Educational purposes, experimentation, and as a foundational block for further specialization.
+
+## How to Get Started with GGUF
+
+This model is provided in GGUF format, making it easy to run locally.
+
+**1. Download the GGUF file:**
+   You can find the GGUF file(s) in the "[Files and versions](https_url_del_repositorio_en_hf/tree/main)" tab of this repository (reemplaza `https_url_del_repositorio_en_hf` con el enlace real a tu repo). Look for files ending with `.gguf`. For example: `math-mini-0.6b-preview-q4_K_M.gguf` (o el nombre exacto de tu archivo).
+
+**2. Using with `llama.cpp` (Example):**
+
+   First, ensure you have `llama.cpp` compiled.
+   ```bash
+   git clone [https://github.com/ggerganov/llama.cpp.git](https://github.com/ggerganov/llama.cpp.git)
+   cd llama.cpp
+   make