THIRD_PARTY_NOTICES.md

Third-party notices

This release bundles no third-party model weights and no third-party source code. The components below are required at runtime and must be obtained by the user under their own licenses. See README.md §4.

ESM2-650M — facebook/esm2_t33_650M_UR50D

Used frozen (never fine-tuned) as the sequence-context model: it provides the reference-process peptide prior and the plan head's anchor/local-context features.

• Publisher: Meta AI (Fundamental AI Research Protein Team)
• Weights: not redistributed here; download from Hugging Face.
• License: the ESM2 model license from Meta. Review it before redistributing weights or derivatives.
• Reference: Lin et al., "Evolutionary-scale prediction of atomic-level protein structure with a language model", Science 379 (2023).

PeptiVerse — peptide property oracles

Supplies the permeability-penetrance predictor that defines the main training objective, plus the monitored toxicity / hemolysis / half-life predictors.

• Weights and source: not redistributed here; obtain the PeptiVerse distribution separately.
• License: as specified by the PeptiVerse authors.

PeptideCLM-23M — aaronfeller/PeptideCLM-23M-all

Required. Supplies SMILES embeddings for several PeptiVerse predictors selected by the official basic_models.txt manifest (including the half-life and nonfouling models).

• Weights: not redistributed here; download from Hugging Face.
• License: as published with the model.

ChemBERTa-77M — DeepChem/ChemBERTa-77M-MLM

Required. Supplies SMILES embeddings for the permeability-penetrance predictor that defines the main training objective, plus the toxicity, PAMPA and Caco-2 models.

• Weights: not redistributed here; download from Hugging Face.
• License: as published by DeepChem.
• Reference: Chithrananda et al., "ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction" (2020).

Python dependencies

Declared in requirements.txt and installed from PyPI, each under its own license:

Package	License
PyTorch	BSD-3-Clause
NumPy	BSD-3-Clause
PyYAML	MIT
RDKit	BSD-3-Clause
transformers (Hugging Face)	Apache-2.0

The PeptiVerse distribution brings its own further dependencies (scikit-learn, XGBoost, MAPIE, pandas, joblib and others); those are governed by their respective licenses and are not declared by this package.

Data

No dataset is included in this release. The processed training and validation splits are handled separately; nothing here downloads, reconstructs or redistributes data. See data/README.md.