Instructions to use inclusionAI/Ling-1T with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use inclusionAI/Ling-1T with Transformers:

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

pipe = pipeline("text-generation", model="inclusionAI/Ling-1T", 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-1T", trust_remote_code=True, dtype="auto")

Inference
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use inclusionAI/Ling-1T with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "inclusionAI/Ling-1T"
# 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-1T",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/inclusionAI/Ling-1T

SGLang

How to use inclusionAI/Ling-1T 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-1T" \
    --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-1T",
		"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-1T" \
        --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-1T",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use inclusionAI/Ling-1T with Docker Model Runner:
```
docker model run hf.co/inclusionAI/Ling-1T
```

Update technical report citation information

#17

by RichardBian - opened Nov 4, 2025

base: refs/heads/main

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from: refs/pr/17

Discussion Files changed

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README.md +16 -1

README.md CHANGED Viewed

@@ -270,4 +270,19 @@ This code repository is licensed under [the MIT License](https://github.com/incl
 ## FAQ
 Recommended temperature? **0.7**
-Recommended top_p? **0.95**

 ## FAQ
 Recommended temperature? **0.7**
+Recommended top_p? **0.95**
+## Citation
+If you find our work helpful, feel free to give our paper a citation.
+```bibtex
+@article{Ling-Team2025,
+  author = {Ling-Team and 141 others},
+  title = {{Every Activation Boosted: Scaling General Reasoner to 1 Trillion Open Language Foundation}},
+  journal = {arXiv preprint arXiv:2510.22115},
+  eprint = {2510.22115},
+  archivePrefix = {arXiv},
+  primaryClass = {cs.CL},
+  year = {2025},
+  doi = {10.48550/arXiv.2510.22115},
+  url = {https://arxiv.org/abs/2510.22115}
+}