初始化项目，由ModelHub XC社区提供模型

Model: UMCU/MedLlama.nl
Source: Original Platform

README.md

@@ -0,0 +1,44 @@
+---
+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}, 
+}
+```