Text Generation
PEFT
lora
trl
naming
brand-generation
controllable-generation
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# Validation Guide

## GPU preflight

Before training, run:

```bash
python scripts/preflight_gpu.py
```

or:

```bash
make preflight
```

Expected output:

```text
GPU_PREFLIGHT_PASS
```

This checks:

- PyTorch version
- CUDA availability
- GPU name
- total VRAM
- compute capability
- minimum T4-class VRAM

## GPU smoke test

The intended GPU smoke test is:

```bash
python scripts/smoke_test.py
```

This loads `Qwen/Qwen2.5-1.5B-Instruct`, runs 15 LoRA SFT steps on 100 examples, generates one candidate, and prints `SMOKE_PASS`.

From the agent environment this could not be executed because GPU/HF Jobs execution was repeatedly rejected.

## CPU static validation

For environments without a GPU, run:

```bash
git clone https://huggingface.co/krystv/nomen-ai
cd nomen-ai
pip install -e . datasets trl peft transformers rapidfuzz pyphen PyYAML
python tests/test_static.py
```

This validates:

- 20+ root families are present.
- Control token prompt construction.
- Syllable/character utilities.
- Anti-duplication matrix.
- Synthetic example generation.
- SFT dataset schema.
- DPO dataset schema.
- Current TRL `SFTConfig` and `DPOConfig` argument names used by the training scripts.

Expected output:

```text
CPU_STATIC_VALIDATION_PASS
```