初始化项目，由ModelHub XC社区提供模型

Model: UMCU/MedLlama.nl
Source: Original Platform

.gitattributes

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README.md

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+---
+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}, 
+}
+```

config.json

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+{
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 128000,
+  "eos_token_id": [
+    128001,
+    128008,
+    128009
+  ],
+  "head_dim": 64,
+  "hidden_act": "silu",
+  "hidden_size": 2048,
+  "initializer_range": 0.02,
+  "intermediate_size": 8192,
+  "max_position_embeddings": 131072,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 16,
+  "num_key_value_heads": 8,
+  "pad_token_id": 128009,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": {
+    "factor": 32.0,
+    "high_freq_factor": 4.0,
+    "low_freq_factor": 1.0,
+    "original_max_position_embeddings": 8192,
+    "rope_type": "llama3"
+  },
+  "rope_theta": 500000.0,
+  "tie_word_embeddings": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.52.4",
+  "use_cache": true,
+  "vocab_size": 128256
+}

generation_config.json

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+{
+  "bos_token_id": 128000,
+  "do_sample": true,
+  "eos_token_id": [
+    128001,
+    128008,
+    128009
+  ],
+  "temperature": 0.6,
+  "top_p": 0.9,
+  "transformers_version": "4.45.0.dev0"
+}

model.safetensors

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special_tokens_map.json

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+{
+  "bos_token": {
+    "content": "<|begin_of_text|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "<|eot_id|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}