personalitylinmult.model

The public, pip-install-only entry point: load a champion model by id.

PersonalityModel.from_pretrained(model_id) downloads a champion checkpoint from the public HF Hub model repo and wraps it for prediction – no MLflow, no repo clone, no external config. This is deliberately the only public model class: a checkpoint already knows whether it is a single-stream LinT or a cross-modal LinMulT (see FiPredictor), so exposing separate PersonalityLinT/PersonalityLinMulT classes would force a caller to track architecture per id for no benefit – this class reads it off the checkpoint instead.

Model ids follow {features joined by "_", multiword feature names use "-"}_best-{metric}, e.g. "wavlm_best-ccc" (LinT, audio only) or "wavlm-emotion2vec_best-ccc" (LinMulT, audio fusion) – the same convention used for the MLflow registered-model names (see personalitylinmult.inference.register_models) and the HF model repo filenames.

Attributes

logger	Module-level logger.
HF_MODEL_REPO	The public HF Hub model repo champion checkpoints are published to.

Classes

PersonalityModel

A champion FI model, loaded by id from the public HF Hub repo.

Module Contents

personalitylinmult.model.logger

Module-level logger.

personalitylinmult.model.HF_MODEL_REPO = 'fodorad/personalitylinmult-fi-models'

The public HF Hub model repo champion checkpoints are published to.

class personalitylinmult.model.PersonalityModel(predictor: personalitylinmult.inference.predictor.FiPredictor)

A champion FI model, loaded by id from the public HF Hub repo.

Parameters:

predictor (FiPredictor) – The loaded predictor to wrap.

property feature_names: list[str]

Features this model consumes, in input order.

property traits: list[str]

Trait names, in output-column order.

classmethod from_pretrained(model_id: str, revision: str | None = None) → PersonalityModel

Download (or reuse the cached) champion checkpoint and load it.

Parameters:

• model_id (str) – A champion id, e.g. "wavlm_best-ccc" or "avt_best-ccc". See the module docstring for the naming convention.

• revision (str | None) – HF Hub revision (branch/tag/commit); None uses the repo’s default branch.

Returns:

Ready to predict.

Return type:

PersonalityModel

predict(features: dict[str, numpy.ndarray]) → dict[str, float]

Predict Big Five scores for one sample.

Parameters:

features (dict[str, np.ndarray]) – One (T, F) array per feature the model expects (see feature_names).

Returns:

{trait: score}, in the model’s trait order.

Return type:

dict[str, float]