DogeAI-v1.5-Coder (ONNX)
This is an ONNX version of AxionLab-official/DogeAI-v1.5-Coder. It was automatically converted and uploaded using this Hugging Face Space.
Usage with Transformers.js
See the pipeline documentation for text-generation: https://huggingface.co/docs/transformers.js/api/pipelines#module_pipelines.TextGenerationPipeline
🐶 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
