Instructions to use TCMLLM/Lingdan-4B-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use TCMLLM/Lingdan-4B-Base with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="TCMLLM/Lingdan-4B-Base")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("TCMLLM/Lingdan-4B-Base")
model = AutoModelForCausalLM.from_pretrained("TCMLLM/Lingdan-4B-Base", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=256)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use TCMLLM/Lingdan-4B-Base with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "TCMLLM/Lingdan-4B-Base"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "TCMLLM/Lingdan-4B-Base",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/TCMLLM/Lingdan-4B-Base

SGLang

How to use TCMLLM/Lingdan-4B-Base with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "TCMLLM/Lingdan-4B-Base" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "TCMLLM/Lingdan-4B-Base",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "TCMLLM/Lingdan-4B-Base" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "TCMLLM/Lingdan-4B-Base",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use TCMLLM/Lingdan-4B-Base with Docker Model Runner:
```
docker model run hf.co/TCMLLM/Lingdan-4B-Base
```

TCMLLM commited on 1 day ago

Commit

22b6010

verified ·

1 Parent(s): d8f30f8

Link arXiv paper and preserve both Lingdan citations

Browse files

README-only: add arXiv entry points, citation metadata and versioned evaluation sources.

Files changed (1) hide show

README.md +8 -4

README.md CHANGED Viewed

@@ -26,6 +26,7 @@ tags:
 </p>
 <p align="center">
   <a href="https://huggingface.co/collections/TCMLLM/lingdan-v2"><img src="https://img.shields.io/badge/Models-Hugging_Face-FFD21E?logo=huggingface&logoColor=black" alt="Hugging Face models" /></a>
   <a href="https://modelscope.cn/collections/TCMAIBJTU/Lingdan-V2"><img src="https://img.shields.io/badge/Models-ModelScope-624AFF" alt="ModelScope models" /></a>
   <a href="https://github.com/TCMAI-BJTU/LingLan"><img src="https://img.shields.io/badge/Benchmark-LingLan-2A8F5B" alt="LingLan benchmark" /></a>
@@ -33,7 +34,7 @@ tags:
   <a href="https://github.com/TCMAI-BJTU/Lingdan-V2/blob/main/LICENSE"><img src="https://img.shields.io/badge/License-Apache--2.0-D22128" alt="Apache License 2.0" /></a>
 </p>
-[Model](#model-details) · [Quickstart](#quickstart) · [vLLM](#vllm-deployment) · [Citation](#citation)
 ## Model Details
@@ -142,14 +143,17 @@ Lingdan-V2 model weights and project-owned documentation and images are released
 ## Citation
-Cite Lingdan-V2 and the earlier Lingdan work:
 ```bibtex
 @misc{hua2026lingdanv2,
   title  = {{Lingdan-V2}: Large language models for clinically grounded reasoning in traditional Chinese medicine},
   author = {Hua, Rui and Wei, Yu and Jin, Ziri and Sun, Zhuo and Chang, Kai and Xia, Jianan and Shu, Zixin and Li, Xiaodong and Jia, Dongmei and Dong, Fei and Zhang, Runshun and Yu, Jian and Xu, Hao and Yu, Haibin and Li, Jiansheng and Liu, Baoyan and Wang, Wenjia and Zhou, Xuezhong},
   year   = {2026},
-  url    = {https://github.com/TCMAI-BJTU/Lingdan-V2}
 }
 @article{hua2024lingdan,
@@ -166,6 +170,6 @@ Cite Lingdan-V2 and the earlier Lingdan work:
 ## Related Links
-[GitHub](https://github.com/TCMAI-BJTU/Lingdan-V2) · [Hugging Face collection](https://huggingface.co/collections/TCMLLM/lingdan-v2) · [ModelScope collection](https://modelscope.cn/collections/TCMAIBJTU/Lingdan-V2) · [LingLan benchmark](https://github.com/TCMAI-BJTU/LingLan)
 For task prompts and thinking-mode chat, see the [SFT/R1 guide](https://github.com/TCMAI-BJTU/Lingdan-V2#task-prompts).

 </p>
 <p align="center">
+  <a href="https://arxiv.org/abs/2610.14705"><img src="https://img.shields.io/badge/arXiv-2610.14705-B31B1B?logo=arxiv&logoColor=white" alt="Lingdan-V2 paper on arXiv" /></a>
   <a href="https://huggingface.co/collections/TCMLLM/lingdan-v2"><img src="https://img.shields.io/badge/Models-Hugging_Face-FFD21E?logo=huggingface&logoColor=black" alt="Hugging Face models" /></a>
   <a href="https://modelscope.cn/collections/TCMAIBJTU/Lingdan-V2"><img src="https://img.shields.io/badge/Models-ModelScope-624AFF" alt="ModelScope models" /></a>
   <a href="https://github.com/TCMAI-BJTU/LingLan"><img src="https://img.shields.io/badge/Benchmark-LingLan-2A8F5B" alt="LingLan benchmark" /></a>
   <a href="https://github.com/TCMAI-BJTU/Lingdan-V2/blob/main/LICENSE"><img src="https://img.shields.io/badge/License-Apache--2.0-D22128" alt="Apache License 2.0" /></a>
 </p>
+[Paper](https://arxiv.org/abs/2610.14705) · [Model](#model-details) · [Quickstart](#quickstart) · [vLLM](#vllm-deployment) · [Citation](#citation)
 ## Model Details
 ## Citation
+Please cite Lingdan-V2 and the earlier Lingdan work:
 ```bibtex
 @misc{hua2026lingdanv2,
   title  = {{Lingdan-V2}: Large language models for clinically grounded reasoning in traditional Chinese medicine},
   author = {Hua, Rui and Wei, Yu and Jin, Ziri and Sun, Zhuo and Chang, Kai and Xia, Jianan and Shu, Zixin and Li, Xiaodong and Jia, Dongmei and Dong, Fei and Zhang, Runshun and Yu, Jian and Xu, Hao and Yu, Haibin and Li, Jiansheng and Liu, Baoyan and Wang, Wenjia and Zhou, Xuezhong},
   year   = {2026},
+  eprint = {2610.14705},
+  archivePrefix = {arXiv},
+  primaryClass = {cs.CL},
+  url    = {https://arxiv.org/abs/2610.14705}
 }
 @article{hua2024lingdan,
 ## Related Links
+[Paper](https://arxiv.org/abs/2610.14705) · [GitHub](https://github.com/TCMAI-BJTU/Lingdan-V2) · [Hugging Face collection](https://huggingface.co/collections/TCMLLM/lingdan-v2) · [ModelScope collection](https://modelscope.cn/collections/TCMAIBJTU/Lingdan-V2) · [LingLan benchmark](https://github.com/TCMAI-BJTU/LingLan)
 For task prompts and thinking-mode chat, see the [SFT/R1 guide](https://github.com/TCMAI-BJTU/Lingdan-V2#task-prompts).