---
license: gpl-3.0
datasets:
- UMCU/DutchMedicalTextV3
language:
- nl
base_model:
- meta-llama/Llama-3.2-1B-Instruct
pipeline_tag: text-generation
tags:
- medical
---

Llama-3.2-1B-Instruct, with domain adapted pretraining (DAPT), also called Continuous Pre-training (CPT) on a generic Dutch medical corpus.

Training for  on the Dutch medical corpus, with a 256 batch size, maximally 1024 sequence length during training and a linear-cosine schedul, with 100 cycles per 
250M steps, with LRmax=1e-4 and 100K warmup steps, AdamW for optimization. 

Currently at 5.5 perplexity, could still use more training. 

Planned: on-premise continuous pre-training on Dutch clinical texts. 

To use for text-generation;

```py
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("UMCU/MedLlama.nl")
model = AutoModelForCausalLM.from_pretrained("UMCU/MedLlama.nl", torch_dtype=torch.float16)
```

If you use this model please cite with

```bibtex
@misc{vanes2026languagecorporadutchmedical,
      title={Language corpora for the Dutch medical domain}, 
      author={B. van Es},
      year={2026},
      eprint={2604.25374},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2604.25374}, 
}
```
