Instructions to use jimtyler/pseng-14b-preview with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use jimtyler/pseng-14b-preview with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir pseng-14b-preview jimtyler/pseng-14b-preview
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
PSEng-14B-preview: iteration 500 selected
Selected on the validation curve alone, before any dev score existed.
| iter | val loss |
|---|---|
| 150 | 0.275 |
| 200 | 0.274 |
| 250 | 0.274 |
| 300 | 0.259 |
| 350 | 0.270 |
| 400 | 0.292 |
| 450 | 0.253 |
| 500 | 0.243 |
| 550 | 0.286 |
Rule, as in v1: minimum validation loss; ties break toward fewer iterations. Iteration 500 is the minimum over the observed curve.
Training was stopped at iteration ~560 of a planned 1,200 rather than run to completion. Reason, recorded plainly: sustained 14B QLoRA on this machine drains the battery ~30 points/hour even on AC (the 96W adapter cannot keep up), and the curve had shown no improvement past 500 across three validation points. The remaining iterations were judged not worth the power. This is a preview artifact; the Phase 2 sweep revisits schedule length on a rested machine.
Note the curve is noisy (0.259 at 300, 0.292 at 400, 0.243 at 500), so "500 is best" is a weak claim over a shallow, jittery minimum, not evidence of a well-converged optimum.
Base: models/phi-4-4bit (QLoRA; adapters trained against the quantized base). Corpus: data/phi_lite, 517 train / 43 valid.