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

Libraries

How to use inclusionAI/Ring-1T-preview with Transformers:

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

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

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use inclusionAI/Ring-1T-preview with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/inclusionAI/Ring-1T-preview

SGLang

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

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

I would like to use this model on my ipad, but can't find it in the appstore, can someone please help me?

by evewashere - opened Oct 3, 2025

Discussion

evewashere

Oct 3, 2025

xscMpOV

Oct 6, 2025

also looking to run this locally on my samsung smart fridge, pls fix

Enderchef

Oct 6, 2025

Oh, it's super easy! They just forget to mention in the README.

Get an iPad.
Pick up a few dozen NVIDIA H200s. (Don't worry, they're on sale at your local Best Buy for a few bucks each.)
You'll need a small, liquid-cooled, data center to power them. (You can probably just clear out your basement.)
Set up the whole thing in the back of your Samsung Smart Fridge or iPad for optimal thermal performance.
Once all that's done, just refresh the App Store page. It should pop right up next to Sora's new app. You're welcome!

21world

Oct 7, 2025

•

edited Oct 7, 2025

may work from ssd ,sdcards but with very very slow inference speed ,if active parameters are lower this speedup ,use llama.cpp with mmap and terminal app(termux on android devices),i do not have apple device to test but on android device may work,faster ssd /sdcard faster inference,so problem is in low read speed of ssd and sdcards available

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