metadata

datasets:
  - Sweaterdog/Andy-4-base
  - Sweaterdog/Andy-4-ft
  - Sweaterdog/Andy-base-2
language:
  - en
base_model:
  - HuggingFaceTB/SmolLM2-360M-Instruct
tags:
  - gaming
  - minecraft
  - mindcraft

🧠 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.

These are the LoRA files for the model

⚠️ 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

📊 Training Regimen

Andy‑4‑base‑1 dataset
- Epochs: 2
- Learning Rate: 5e-5
- Dataset Size: 47.4k
Andy‑4‑base-2 dataset
- Epochs: 2
- Learning Rate: 7e-5
- Dataset Size: 49.2k
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

🚀 Installation

Andy-4-tiny is an Edge-case model, built to run on the CPU and use minimal ram

Quantization	RAM Required
F16	CPU
Q8_0	CPU
Q4_K_M	CPU

1. Installation directly on Ollama

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

2. Manual Download & Modelfile

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.

Edit

Change

FROM YOUR/PATH/HERE

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

Create
```
ollama create andy-4-tiny -f Modelfile
```

This registers the Andy‑4-tiny model locally.

📌 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

⚖️ License

See Andy 1.0 License.

This work uses data and models created by @Sweaterdog.