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# Forge Coder v1.21.11
A specialized code generation model fine-tuned for Minecraft Forge mod development.
## Model Details
| Property | Value |
|----------|-------|
| **Base Model** | deepseek-ai/deepseek-coder-6.7b-instruct |
| **Fine-tuning Method** | LoRA (r=64, alpha=128) |
| **Trainable Parameters** | 159.9M (2.3% of total) |
| **Forge Version** | 1.21.11 |
| **Minecraft Version** | 1.21.11 |
| **MCP Version** | 20251209.095502 |
## Training Data
- **Source Code**: 27 popular Forge mod repositories
- **Documentation**: Official Forge documentation
- **Total Java Files**: 22,916
- **Training Samples**: 13,936
- **Validation Samples**: 734
### Included Mods
Applied Energistics 2, JustEnoughItems, TerraFirmaCraft, Mekanism, Create,
Thermal Expansion/Foundation, RFTools, Botania, Quark, Tinkers' Construct,
Immersive Engineering, Twilight Forest, and more.
## Training Metrics
| Metric | Value |
|--------|-------|
| Training Time | 9h 12m |
| Final Train Loss | 0.27 |
| Final Eval Loss | 0.325 |
| Token Accuracy | 92.5% |
| Epochs | 3 |
## Capabilities
The model is specialized in:
- Block and Item creation
- Entity programming
- GUI/Screen development
- Network packet handling
- World generation
- Event handling
- Registry systems
- Capability API
- Recipe systems
- Rendering code
- Data generation
## Usage
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel
base_model = "deepseek-ai/deepseek-coder-6.7b-instruct"
adapter_path = "path/to/forge-coder-v1.21.11"
tokenizer = AutoTokenizer.from_pretrained(adapter_path)
model = AutoModelForCausalLM.from_pretrained(base_model, torch_dtype=torch.bfloat16)
model = PeftModel.from_pretrained(model, adapter_path)
prompt = """### System:
You are an expert Minecraft Forge mod developer.
### User:
Write a simple custom block class for Minecraft Forge 1.21.11
### Assistant:
"""
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=512)
print(tokenizer.decode(outputs[0]))
```
## Version History
- **v1.21.11** (2024-12-18): Initial release for MC 1.21.11 / Forge 1.21.11
## License
This model is released under the same license as the base model (deepseek-coder).
Training data sourced from open-source repositories under various permissive licenses.
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