Instructions to use inclusionAI/Ring-flash-linear-2.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use inclusionAI/Ring-flash-linear-2.0 with Transformers:

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

pipe = pipeline("text-generation", model="inclusionAI/Ring-flash-linear-2.0", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("inclusionAI/Ring-flash-linear-2.0", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use inclusionAI/Ring-flash-linear-2.0 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "inclusionAI/Ring-flash-linear-2.0"
# 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-flash-linear-2.0",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/inclusionAI/Ring-flash-linear-2.0

SGLang

How to use inclusionAI/Ring-flash-linear-2.0 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-flash-linear-2.0" \
    --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-flash-linear-2.0",
		"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-flash-linear-2.0" \
        --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-flash-linear-2.0",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use inclusionAI/Ring-flash-linear-2.0 with Docker Model Runner:
```
docker model run hf.co/inclusionAI/Ring-flash-linear-2.0
```

curryandsun commited on Sep 25, 2025

Commit

cbcf949

verified ·

1 Parent(s): 478273f

Update README.md

Browse files

Files changed (1) hide show

README.md +3 -5

README.md CHANGED Viewed

@@ -74,9 +74,9 @@ What is truly exciting is that in the comparison with Qwen3-32B, Ring-flash-line
 <div align="center">
-|     **Model**      | **#Total Params** | **#Activated Params** | **Context Length** | **Download** |
-| :----------------: | :---------------: | :-------------------: | :----------------: | :----------: |
-| Ring-flash-linear-2.0 |       100B       |         6.1B         |        128K         |      [🤗 HuggingFace](https://huggingface.co/inclusionAI/Ring-flash-linear-2.0) <br>[🤖 Modelscope](https://modelscope.cn/models/inclusionAI/Ring-flash-linear-2.0)|
 </div>
 ## Quickstart
@@ -86,8 +86,6 @@ What is truly exciting is that in the comparison with Qwen3-32B, Ring-flash-line
 ```bash
 pip install flash-linear-attention==0.3.2
 pip install transformers==4.56.1
-pip install sgl-kernel==0.3.9.post2
-pip install vllm==0.10.2
 ```
 ### 🤗 Hugging Face Transformers

 <div align="center">
+|     **Model**      | **Context Length** | **Download** |
+| :----------------: | :----------------: | :----------: |
+| Ring-flash-linear-2.0 |        128K         |      [🤗 HuggingFace](https://huggingface.co/inclusionAI/Ring-flash-linear-2.0) <br>[🤖 Modelscope](https://modelscope.cn/models/inclusionAI/Ring-flash-linear-2.0)|
 </div>
 ## Quickstart
 ```bash
 pip install flash-linear-attention==0.3.2
 pip install transformers==4.56.1
 ```
 ### 🤗 Hugging Face Transformers