Sweaterdog/Andy-4-tiny

🧠 Andy‑4-tiny 🐜

Andy‑4-tiny is an 360 Million‑parameter specialist model tuned for Minecraft gameplay via the Mindcraft framework. The Current version of Andy-4-tiny is Andy-4-tiny-0522.

⚠️ Certification:
Andy‑4 is not yet certified by the Mindcraft developers. Use in production at your own discretion.

🔍 Model Specifications

• Parameters: 360M

• Training Hardware: 1 × NVIDIA RTX 3070

• Duration: ~ 36 hours total

• Data Volumes:

  • Messages: 179,384
  • Tokens: 425,535,198
  • Conversations: 62,149

• Base Architecture: SmolLM2

• License: Andy 1.0 License

• Repository: https://huggingface.co/Sweaterdog/Andy‑4

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📊 Training Regimen

1. Andy‑4‑base‑1 dataset

   • Epochs: 2
   • Learning Rate: 5e-5
   • Dataset Size: 47.4k

2. Andy‑4‑base-2 dataset

   • Epochs: 2
   • Learning Rate: 7e-5
   • Dataset Size: 49.2k

3. Fine‑tune (FT) dataset

   • Epochs: 2.5
   • Learning Rate: 2e-5
   • Dataset Size: 4.12k

• Optimizer: AdamW_8bit with cosine decay
• Quantization: 4‑bit (bnb-4bit) for inference
• Warm Up Steps: 0.1% of each dataset

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🚀 Installation

Andy-4-tiny is an Edge-case model, built to run on the CPU and use minimal ram. These are the requirements to Run Them, not to use them while Minecraft is also running.

Quantization	RAM Required
F16	CPU 2GB
Q8_0	CPU 1GB
Q4_K_M	CPU 0.8GB

1. Installation directly on Ollama

1. Visit Andy-4 on Ollama
2. Copy the command after choosing model type / quantization
3. Run the command in the terminal
4. Set the profile's model to be what you installed, such as ollama/sweaterdog/andy-4:tiny-q8_0

2. Manual Download & Modelfile

1. Download

   • From the HF Files tab, grab your chosen .GGUF quant weights (e.g. Andy-4-tiny.Q4_K_M.gguf).
   • Download the provided Modelfile.

2. Edit

   Change

   FROM YOUR/PATH/HERE
   

   to

   FROM /path/to/Andy-4-tiny.Q4_K_M.gguf
   

Optional: Increase the parameter num_ctx to a higher value for longer conversations if you:

A. Have extra VRAM

B. Quantized the context window

C. Can use a smaller model

3. Create

   ollama create andy-4-tiny -f Modelfile
   

This registers the Andy‑4-tiny model locally.

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📌 Acknowledgments

Click to expand

• Data & Models by: @Sweaterdog
• Framework: Mindcraft (https://github.com/kolbytn/mindcraft)
• LoRA Weights: https://huggingface.co/Sweaterdog/Andy-4-LoRA
• *Explicit credit is not granted to Meta since this model was trained off of a slightly different architecture, from DeepSeek-R1

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⚖️ License

See Andy 1.0 License.

This work uses data and models created by @Sweaterdog.