RESEARCH / EDUCATIONAL QA ONLY. This adapter is NOT a medical device, NOT a diagnostic tool, and NOT a substitute for a qualified radiologist. It MUST NOT be used for clinical decision-making, screening, triage, or patient care. Outputs of the adapted model are frequently wrong.

This repository holds the unmerged QLoRA LoRA adapter I trained over google/medgemma-1.5-4b-it for the CXR Draft Auditor project. I pushed it to the Hub as a safety copy BEFORE the merge step, following the procedure I use across the project (push the adapter first, then merge into a clean bf16 base and verify a non-trivial weight delta, so a silent merge can never be published). Applying this adapter to the bf16 base model reproduces the merged v1 model, alex-feeel/medgemma-cxr-auditor. That v1 model originally served the CXR Draft Auditor demo Space, but as of 2026-06-12 it has been superseded as served by the v2 derivative (alex-feeel/medgemma-cxr-auditor-v2), which won the held-out head-to-head; I keep v1 for reference and reproducibility.

Adapter details

Developed by: Aleksandr Filippov (Build Small Hackathon, June 2026).
Base model: google/medgemma-1.5-4b-it (HAI-DEF, gated; you must accept the HAI-DEF terms on the base repository to download it).
Corresponding merged model: alex-feeel/medgemma-cxr-auditor (v1, superseded as served by v2 on 2026-06-12).
Adapter type: LoRA (PEFT), rank 16, alpha 16, dropout 0.0, no bias, task type CAUSAL_LM, saved with PEFT 0.19.1.
Target modules: q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj (attention and MLP projections; by name match this covers both the Gemma-3 language tower and the vision-tower attention).
Training: TRL SFTTrainer + PEFT QLoRA (4-bit NF4 via bitsandbytes), learning rate 2e-4, batch size 1, gradient accumulation 8, 1 epoch over approximately 6,800 curated, class-balanced CXR grounding examples, on a single A100 (80 GB) via Hugging Face Jobs.
Contents: adapter_config.json and adapter_model.safetensors (approximately 66 MB), plus the tokenizer and processor configuration files saved alongside the adapter.

For the task description, canonical finding set, output format, training data and licenses, evaluation results, and limitations, see the merged model card: https://huggingface.co/alex-feeel/medgemma-cxr-auditor. No separate evaluation exists for this adapter; the merged v1 and v2 model cards carry the held-out head-to-head results.

How to load with PEFT

python

import torch
from peft import PeftModel
from transformers import AutoModelForImageTextToText, AutoProcessor

base_id = "google/medgemma-1.5-4b-it"  # gated: accept the HAI-DEF terms first
base = AutoModelForImageTextToText.from_pretrained(base_id, dtype=torch.bfloat16)
model = PeftModel.from_pretrained(base, "alex-feeel/medgemma-cxr-auditor-adapter")
processor = AutoProcessor.from_pretrained(base_id)

To reproduce the published merged model, call model.merge_and_unload() on the loaded PeftModel (on the bf16 base, never on a 4-bit quantized base) and verify the merged weights differ non-trivially from the base before using or distributing the result.

License and usage constraints

Identical to the merged model card. This adapter is a MedGemma "Model Derivative" within the meaning of the Health AI Developer Foundations (HAI-DEF) Terms of Use, and the following distribution conditions apply.

HAI-DEF Terms of Use: https://developers.google.com/health-ai-developer-foundations/terms
Prohibited Use Policy (incorporated by reference into the Terms): https://developers.google.com/health-ai-developer-foundations/prohibited-use-policy
Notice file: a NOTICE file is distributed with this repository. It states verbatim: "HAI-DEF is provided under and subject to the Health AI Developer Foundations Terms of Use found at https://developers.google.com/health-ai-developer-foundations/terms".
Agreement propagation: the Section 3.2 use restrictions of the HAI-DEF Terms (including, without limitation, the Clinical Use restriction, the prohibition on uses that would make Google a device manufacturer, and the Prohibited Use Policy) are propagated as an enforceable provision governing the use and further distribution of this adapter. Recipients are hereby notified that their use and any further distribution are subject to Section 3.2.
No endorsement: Google does not endorse this adapter, this software, or its author. "MedGemma", "Gemma", and "Google" are trademarks of Google LLC and are used here only for accurate attribution of the base model.
Any clinical use (diagnosis, screening, triage, treatment, patient management) is out of scope and prohibited.

alex-feeel/medgemma-cxr-auditor-adapter

CXR Draft Auditor - LoRA Adapter for v1 (pre-merge safety copy)

Adapter details

How to load with PEFT

License and usage constraints

Links

alex-feeel/
medgemma-cxr-auditor-adapter