Update README.md

README.md

@@ -4,4 +4,106 @@ language:
 - pt
 base_model:
 - google/gemma-3-270m
----
+---
+
+# 🐶 DogeAI-v1.5-Coder
+
+DogeAI-v1.5-Coder is a **small, experimental code-focused language model** fine-tuned from **Gemma 3 (270M parameters)**.
+
+This model was created as a learning and experimentation project, focusing on **code generation and completion** with limited resources. It is **not intended to compete with large-scale coding models**, but rather to explore how far a compact model can go when domain-focused.
+
+---
+
+## 🔍 Model Details
+
+- **Base model:** Gemma 3 – 270M  
+- **Fine-tuning type:** Supervised fine-tuning (SFT)  
+- **Primary domain:** Programming / code-related text  
+- **Languages:** Mixed (depends on dataset; mainly scripting-style code)  
+- **Parameters:** ~270 million  
+- **Context length:** Limited (inherits base model constraints)
+
+---
+
+## 🎯 Intended Use
+
+DogeAI-v1.5-Coder is best suited for:
+
+- Simple code completion
+- Small scripting examples
+- Educational purposes (learning how fine-tuning works)
+- Research on **small language models**
+- Benchmarking and experimentation
+
+It performs best when:
+- Prompts are short and explicit
+- The task is narrow and well-defined
+- Expectations are aligned with its size
+
+---
+
+## ⚠️ Limitations
+
+This model has **clear and expected limitations**:
+
+- Weak long-range reasoning
+- Inconsistent performance on complex programming tasks
+- Limited generalization outside the training distribution
+- Not reliable for production or critical systems
+
+These limitations are a direct consequence of its **small scale and experimental nature**.
+
+---
+
+## 🧪 Training Notes
+
+- The model was fine-tuned on a custom dataset focused on code-related text.
+- No reinforcement learning or advanced alignment techniques were used.
+- The goal was experimentation and learning, not optimization for benchmarks.
+
+---
+
+## 📚 Why This Model Exists
+
+DogeAI-v1.5-Coder exists as a **learning artifact**.
+
+It represents:
+- Early experimentation with fine-tuning
+- Exploration of low-parameter models
+- A step in understanding data quality, formatting, and model behavior
+
+Small models are valuable tools for understanding how language models actually work.
+
+---
+
+## 🚫 What This Model Is NOT
+
+- ❌ A replacement for large coding assistants
+- ❌ A reasoning-focused model
+- ❌ Production-ready
+- ❌ Instruction-following at a high level
+
+---
+
+## 📜 License
+
+This model follows the same license as its base model (Gemma).  
+Please ensure compliance with the original license when using or redistributing.
+
+---
+
+## 🙌 Acknowledgements
+
+- Google Gemma team for the base model
+- The open-source ML community
+
+---
+
+## 🧠 Final Note
+
+DogeAI-v1.5-Coder is small, imperfect, and honest.  
+Its value lies in experimentation, not performance.
+
+Sometimes, understanding the limits teaches more than chasing scale.
+
+MADE BY AXIONLAB