Laya vs Vela 2.0

Laya

Apache-2.0 code and weights, installed with pip install laya, with Python 3.10 to 3.13 tested in CI. Base checkpoints score 0.362 and 0.352 on the maintainers' typed-decisions benchmark against a 0.318 random baseline, so it needs fine-tuning.

Vela 2.0

One self-hosted call answers routing, prompt-attack, personal-data and unsupported-claim questions with probabilities and character offsets, under Apache-2.0 with SHA-256 manifests. The models are days old and carry no Hub version tags, and the three larger sizes keep 74 to 89 per cent of their Decision 2.0 bases on the Jev Decision Index by the authors' figures.

Laya

1. Set LAYA_API_KEY before starting laya-serve. It listens on every interface by default
2. Gate on answer_confidence, not confidence, which measures entropy and doesn't match Jev's field
3. Shortlist choice questions with more than about 20 options using predict_shortlist or the laya_shortlist tool
4. Use semantic or opaque labels such as A and B, not yes and no, in choice questions. The checkpoints can follow the label text
5. Pass model="multilingual" and max_len=8192 for long documents. The English checkpoint stops at 512 tokens

Vela 2.0

1. Pin a commit hash with revision= when loading from the Hub. The repositories have no tags and main has changed since launch
2. Send the served name in model, for example vllm-sr/Vela-2.0-4B. The bundled server answers 422 to any other name
3. Name span questions pii, halu or toxic, or set "head": "router", to get the trained router head. Other labels go to the broad head
4. Keep input under 16,384 tokens a sequence (8,192 on the 0.3B). The bundled server answers 413 when the questions alone don't fit
5. Set VELA2_API_KEY before binding the bundled server beyond 127.0.0.1, and keep the model runtime on a trusted network