File size: 1,713 Bytes
741f011
 
 
8b717f7
 
741f011
8b717f7
 
 
 
 
741f011
 
 
 
 
 
8b717f7
 
 
 
741f011
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
8b717f7
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
---
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).