Update experiment model index

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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:

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

Each run directory is directly loadable as a Transformers subfolder:

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.