---
library_name: transformers
tags:
- biology
- medical
- biomedical
- natural-language-processing
- relation-extraction
- named-entity-recognition
- question-answering
- synthetic-biology
- synthetic-data
- low-resource
- biomedbert
---

# MultiAgent4SyntheticBioNLP experiment models

This repository archives Hugging Face models from multiple experiments and
datasets in the MultiAgent4SyntheticBioNLP project. Remote paths mirror the
project hierarchy beginning below `experiments/`, while local-only `model` or
`models` container directories are removed.

For example:

```text
local:  overall-results/phosphorylation/model/<run>/model/*
remote: overall-results/phosphorylation/<run>/*
```

Each run directory is directly loadable as a Transformers subfolder:

```python
from transformers import AutoModel, AutoTokenizer

repo_id = "OWNER/REPOSITORY"
subfolder = "overall-results/phosphorylation/RUN_NAME"
tokenizer = AutoTokenizer.from_pretrained(repo_id, subfolder=subfolder)
model = AutoModel.from_pretrained(repo_id, subfolder=subfolder)
```

Each run contains only its final inference-model artifacts. Per-run
`metrics.json`, `prepared-data/`, prepared training CSVs, and checkpoints are
not uploaded.

## Intended use and limitations

These are research artifacts for studying synthetic-data augmentation in
biomedical NLP. They are not intended for clinical diagnosis or treatment
decisions. Review the corresponding local experiment documentation, metrics,
and data-selection manifest before reuse.