| --- |
| base_model: meta-llama/Llama-3.1-8B-Instruct |
| library_name: transformers |
| license: llama3.1 |
| pipeline_tag: text-generation |
| tags: |
| - drug-combination |
| - relation-extraction |
| - biomedical |
| - llama |
| - chain-of-thought |
| --- |
| |
| # RexDrug-Base |
|
|
| This is the SFT (Supervised Fine-Tuning) base model for **RexDrug**, a chain-of-thought reasoning model for biomedical drug combination relation extraction. |
|
|
| For more details, please refer to the paper: [RexDrug: Reliable Multi-Drug Combination Extraction through Reasoning-Enhanced LLMs](https://huggingface.co/papers/2603.08166). |
|
|
| **Official Code:** [DUTIR-BioNLP/RexDrug](https://github.com/DUTIR-BioNLP/RexDrug) |
|
|
| ## Model Details |
|
|
| - **Base architecture**: [Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) |
| - **Fine-tuning method**: SFT with LoRA (merged) |
| - **Task**: Drug combination relation extraction from biomedical literature |
| - **Relation types**: POS (beneficial), NEG (harmful), COMB (neutral/mixed), NO_COMB (no combination) |
| |
| ## Usage |
| |
| This model is intended to be used with the [RexDrug-adapter](https://huggingface.co/dlutIR/RexDrug-adapter) (LoRA adapter trained via GRPO). See the adapter repository for the full quick start guide. |
| |
| ```python |
| from transformers import AutoTokenizer, AutoModelForCausalLM |
| from peft import PeftModel |
| import torch |
| |
| model = AutoModelForCausalLM.from_pretrained( |
| "dlutIR/RexDrug-base", |
| torch_dtype=torch.bfloat16, |
| device_map="auto", |
| ) |
| model = PeftModel.from_pretrained(model, "dlutIR/RexDrug-adapter") |
| ``` |
| |
| ## License |
|
|
| This model is built upon Llama 3.1 and is subject to the [Llama 3.1 Community License Agreement](https://github.com/meta-llama/llama-models/blob/main/models/llama3_1/LICENSE). |
