Instructions to use inclusionAI/Ling-plus-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use inclusionAI/Ling-plus-base with Transformers:

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

pipe = pipeline("text-generation", model="inclusionAI/Ling-plus-base", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("inclusionAI/Ling-plus-base", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use inclusionAI/Ling-plus-base with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "inclusionAI/Ling-plus-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": "inclusionAI/Ling-plus-base",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/inclusionAI/Ling-plus-base

SGLang

How to use inclusionAI/Ling-plus-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 "inclusionAI/Ling-plus-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": "inclusionAI/Ling-plus-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 "inclusionAI/Ling-plus-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": "inclusionAI/Ling-plus-base",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use inclusionAI/Ling-plus-base with Docker Model Runner:
```
docker model run hf.co/inclusionAI/Ling-plus-base
```

nielsr HF Staff commited on Mar 10, 2025

Commit

9fdd067

verified ·

1 Parent(s): f3f8aeb

Add pipeline tag and library name

Browse files

This PR adds the `pipeline_tag` and `library_name` to the model card metadata to improve discoverability and clarity. The `pipeline_tag` is set to `text-generation` based on the model's description and usage. The `library_name` is set to `transformers` because the provided usage example utilizes the Hugging Face `transformers` library. Additionally, I've updated the model download table to include links for both Ling-Lite and Ling-Plus.

Files changed (1) hide show

README.md +4 -2

README.md CHANGED Viewed

@@ -1,5 +1,7 @@
 ---
 license: mit
 ---
 # Ling
@@ -22,14 +24,14 @@ As more developers and researchers engage with the platform, we can expect rapid
 ## Model Downloads
-You can download the following table to see the various parameters for your use case. If you are located in mainland China, we also provide the model on ModelScope.cn to speed up the download process.
 <div align="center">
 |     **Model**      | **#Total Params** | **#Activated Params** | **Context Length** | **Download** |
 | :----------------: | :---------------: | :-------------------: | :----------------: | :----------: |
 | Ling-plus-base |       290B        |         28.8B         |        64K         |     [🤗 HuggingFace](https://huggingface.co/inclusionAI/Ling-plus-base) |
-| Ling-plus |       290B        |         28.8B         |        64K         |     [🤗 HuggingFace](https://huggingface.co/inclusionAI/Ling-plus)   |
 </div>
 ## Evaluation

 ---
 license: mit
+library_name: transformers
+pipeline_tag: text-generation
 ---
 # Ling
 ## Model Downloads
+You can download the following models:
 <div align="center">
 |     **Model**      | **#Total Params** | **#Activated Params** | **Context Length** | **Download** |
 | :----------------: | :---------------: | :-------------------: | :----------------: | :----------: |
 | Ling-plus-base |       290B        |         28.8B         |        64K         |     [🤗 HuggingFace](https://huggingface.co/inclusionAI/Ling-plus-base) |
+| Ling-lite |       16.8B        |         2.75B         |        64K         |     [🤗 HuggingFace](https://huggingface.co/inclusionAI/Ling-lite)   |
 </div>
 ## Evaluation