Instructions to use TCMLLM/Lingdan-8B-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use TCMLLM/Lingdan-8B-Base with Transformers:

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

pipe = pipeline("text-generation", model="TCMLLM/Lingdan-8B-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-8B-Base")
model = AutoModelForCausalLM.from_pretrained("TCMLLM/Lingdan-8B-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-8B-Base with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "TCMLLM/Lingdan-8B-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-8B-Base",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/TCMLLM/Lingdan-8B-Base

SGLang

How to use TCMLLM/Lingdan-8B-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-8B-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-8B-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-8B-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-8B-Base",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use TCMLLM/Lingdan-8B-Base with Docker Model Runner:
```
docker model run hf.co/TCMLLM/Lingdan-8B-Base
```

TCMLLM commited on 9 days ago

Commit

8e5e842

verified ·

1 Parent(s): 46066f1

Improve model card navigation and result placement

Browse files

Files changed (1) hide show

README.md +2 -9

README.md CHANGED Viewed

@@ -26,21 +26,14 @@ tags:
 </p>
 <p align="center">
   <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>
   <img src="https://img.shields.io/badge/Model_scales-4B_%7C_8B_%7C_14B-0B5394" alt="Model scales: 4B, 8B, and 14B" />
   <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>
-## Contents
-1. [Model Details](#model-details)
-2. [Quickstart](#quickstart)
-3. [vLLM Deployment](#vllm-deployment)
-4. [Data Privacy and Responsible Use](#data-privacy-and-responsible-use)
-5. [License](#license)
-6. [Citation](#citation)
-7. [Related Links](#related-links)
 ## Model Details

 </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>
   <img src="https://img.shields.io/badge/Model_scales-4B_%7C_8B_%7C_14B-0B5394" alt="Model scales: 4B, 8B, and 14B" />
   <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