wesamoyo-20M

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## Architecture Specifications

| Component | Specification | Description |
|-----------|--------------|-------------|
| **Model Type** | MoE Transformer | Mixture-of-Experts design |
| **Total Parameters** | 20B | Architecture capacity |
| **Experts** | 256 total, 8 active | MoE routing configuration |
| **Context Window** | 16,384 tokens | Extended sequence processing |
| **Transformer Blocks** | 61 layers | Network depth |
| **Hidden Dimension** | 7,168 | Feature representation size |
| **Attention Heads** | 128 | Parallel attention computation |
| **LoRA Configuration** | Q: 1,536, KV: 512 | Low-rank adaptation ranks |
| **Vocabulary Size** | 129,280 tokens | Token dictionary |
| **Precision Support** | FP8/BF16 mixed | Training optimization |

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## Training Applications

### Language Processing
- Text generation and completion
- Document summarization
- Multi-language translation
- Content creation and editing

### Code Generation
- Python, JavaScript, TypeScript
- API and library development
- Code documentation
- Script automation

### Reasoning Systems
- Mathematical computation
- Logical problem solving
- Algorithm design
- Data analysis

### Enterprise Solutions
- Technical documentation
- Business analysis reports
- Customer support automation
- Compliance documentation

### Research Development
- MoE routing optimization
- Attention mechanism studies
- Quantization experiments
- Distributed training systems

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## Training Requirements

### Hardware Specifications
- **Minimum**: 40GB GPU memory (A100/H100)
- **Recommended**: 8× A100/H100 cluster
- **Storage**: 100GB+ for datasets
- **Network**: High-speed interconnects

### Data Requirements
- **Pretraining**: 100B+ tokens
- **Fine-tuning**: 1M-10M examples
- **Domain data**: Industry-specific corpora
- **Validation**: 5-10% holdout sets

### Training Timeline
- **Initialization**: 1-2 days setup
- **Pretraining**: 2-4 weeks (multi-GPU)
- **Fine-tuning**: 3-7 days per task
- **Evaluation**: Ongoing validation

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## Quick Start Training