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

Libraries

How to use inclusionAI/Ling-plus with Transformers:

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

pipe = pipeline("text-generation", model="inclusionAI/Ling-plus", 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", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use inclusionAI/Ling-plus with vLLM:

Install from pip and serve model

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

Use Docker

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

SGLang

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

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

zhujiangang commited on Mar 17, 2025

Commit

51bed72

verified ·

1 Parent(s): e7758fc

Update config.json

Browse files

Files changed (1) hide show

config.json +2 -6

config.json CHANGED Viewed

@@ -15,7 +15,7 @@
     "hidden_size": 5376,
     "initializer_range": 0.006,
     "intermediate_size": 12288,
-    "max_position_embeddings": 65536,
     "model_type": "bailing_moe",
     "moe_intermediate_size": 3072,
     "num_experts": 64,
@@ -27,11 +27,7 @@
     "num_key_value_heads": 8,
     "pretraining_tp": 1,
     "rms_norm_eps": 1e-05,
-    "rope_scaling": {
-        "factor": 4.0,
-        "original_max_position_embeddings": 16384,
-        "type": "yarn"
-    },
     "rope_theta": 600000,
     "tie_word_embeddings": false,
     "torch_dtype": "bfloat16",

     "hidden_size": 5376,
     "initializer_range": 0.006,
     "intermediate_size": 12288,
+    "max_position_embeddings": 16384,
     "model_type": "bailing_moe",
     "moe_intermediate_size": 3072,
     "num_experts": 64,
     "num_key_value_heads": 8,
     "pretraining_tp": 1,
     "rms_norm_eps": 1e-05,
+    "rope_scaling": null,
     "rope_theta": 600000,
     "tie_word_embeddings": false,
     "torch_dtype": "bfloat16",