Update README.md

README.md

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----
-license: apache-2.0
----
+---
+license: apache-2.0
+library_name: peft
+pipeline_tag: text-classification
+tags:
+  - biomedical
+  - rag
+  - fact-checking
+  - nli
+  - entailment
+  - peft
+  - lora
+  - medragchecker
+# IMPORTANT:
+# - Do NOT set `base_model` to a local filesystem path. If you want to specify it, use a valid Hugging Face model id (org/name).
+# - Because this repo contains adapters for multiple different base models, `base_model` is intentionally omitted.
+---
+
+# MedRAGChecker Student Checker — LoRA Adapters
+
+This repository hosts **LoRA adapters** for the *checker* component used in the MedRAGChecker project.
+The checker is trained as an NLI-style verifier to classify a **(evidence, claim)** pair into:
+
+- **Entail**
+- **Neutral**
+- **Contradict**
+
+These adapters are intended for **research and evaluation** (e.g., ensembling multiple checkers trained with different base models and/or training recipes such as SFT vs. GRPO).
+
+> This repo contains **adapters only**. You must load each adapter on top of its corresponding **base model**.
+
+---
+
+## Contents
+
+Each adapter subfolder typically includes:
+
+- `adapter_config.json`
+- `adapter_model.safetensors` (or `.bin`)
+
+---
+
+## Available adapters
+
+All adapters live under the `Checker/` directory:
+
+| Adapter subfolder | Base model (HF id) | Training recipe | Notes |
+|---|---|---|---|
+| `Checker/med42-llama3-8b-sft` | `<PUT_BASE_MODEL_ID_HERE>` | SFT |  |
+| `Checker/med42-llama3-8b-grpo` | `<PUT_BASE_MODEL_ID_HERE>` | GRPO |  |
+| `Checker/meditron-sft` | `<PUT_BASE_MODEL_ID_HERE>` | SFT |  |
+| `Checker/meditron-grpo` | `<PUT_BASE_MODEL_ID_HERE>` | GRPO |  |
+| `Checker/PMC_LLaMA_13B-sft` | `<PUT_BASE_MODEL_ID_HERE>` | SFT |  |
+| `Checker/qwen2-med-7b-sft` | `<PUT_BASE_MODEL_ID_HERE>` | SFT |  |
+| `Checker/qwen2-med-7b-grpo` | `<PUT_BASE_MODEL_ID_HERE>` | GRPO |  |
+
+### How to fill the “Base model (HF id)” column
+
+Use a valid Hugging Face Hub model id (format: `org/name`). Examples:
+
+- `meta-llama/Meta-Llama-3-8B-Instruct`
+- `Qwen/Qwen2-7B-Instruct`
+
+If your base model is **not** available on the Hub (only stored locally), you can either:
+1) upload the base model to a private Hub repo and reference that id here, or  
+2) keep this field as `N/A (local)` and document your local loading instructions.
+
+---
+
+## Quickstart: load an adapter with PEFT
+
+```python
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+from peft import PeftModel
+
+# 1) Choose the base model that matches the adapter you want to use
+base_model_id = "<HF_BASE_MODEL_ID>"
+
+# 2) Choose the adapter subfolder inside this repo
+repo_id = "JoyDaJun/Medragchecker-Student-Checker"
+subfolder = "Checker/qwen2-med-7b-sft"  # example
+
+tokenizer = AutoTokenizer.from_pretrained(base_model_id, use_fast=True)
+model = AutoModelForSequenceClassification.from_pretrained(base_model_id)
+model = PeftModel.from_pretrained(model, repo_id, subfolder=subfolder)
+```
+
+> If your checker was trained using a **Causal LM** head instead of a sequence classification head,
+replace `AutoModelForSequenceClassification` with `AutoModelForCausalLM` and use the same prompt/template as in training.
+
+---
+
+## Ensemble usage (optional)
+
+If you trained multiple student checkers, you can ensemble them (e.g., by weighting each checker’s class probabilities using dev-set reliability such as per-class F1).
+This often helps stabilize performance across **Entail / Neutral / Contradict**, especially under class imbalance.
+
+---
+
+## Limitations & responsible use
+
+- **Not medical advice.** Do not use for clinical decision-making.
+- Outputs may reflect biases or errors from training data and teacher supervision.
+- Please evaluate on your target dataset and report limitations clearly.
+
+---
+
+## Citation
+
+If you use these adapters, please cite your MedRAGChecker paper/project:
+
+```bibtex
+@article{medragchecker,
+  title={MedRAGChecker: A Claim-Level Verification Framework for Biomedical RAG},
+  author={...},
+  year={2025}
+}
+```