Instructions to use nex-agi/Nex-N2.5-Pro with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use nex-agi/Nex-N2.5-Pro with Transformers:

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

pipe = pipeline("text-generation", model="nex-agi/Nex-N2.5-Pro")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("nex-agi/Nex-N2.5-Pro")
model = AutoModelForMultimodalLM.from_pretrained("nex-agi/Nex-N2.5-Pro", device_map="auto")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
inputs = processor.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use nex-agi/Nex-N2.5-Pro with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "nex-agi/Nex-N2.5-Pro"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "nex-agi/Nex-N2.5-Pro",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/nex-agi/Nex-N2.5-Pro

SGLang

How to use nex-agi/Nex-N2.5-Pro 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 "nex-agi/Nex-N2.5-Pro" \
    --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": "nex-agi/Nex-N2.5-Pro",
		"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 "nex-agi/Nex-N2.5-Pro" \
        --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": "nex-agi/Nex-N2.5-Pro",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use nex-agi/Nex-N2.5-Pro with Docker Model Runner:
```
docker model run hf.co/nex-agi/Nex-N2.5-Pro
```

00index commited on 8 days ago

Commit

aa66e19

verified ·

1 Parent(s): 11f1e46

Model card: sync github.com/nex-agi/Nex-N2.5 @ 0e5ba9c (HF collection link, Thinking Control section)

Browse files

Files changed (1) hide show

README.md +22 -2

README.md CHANGED Viewed

@@ -12,7 +12,7 @@ library_name: transformers
 <div align="center">
 <p>
   💻 <a href="https://github.com/nex-agi/Nex-N2.5">GitHub</a>&nbsp; · &nbsp;
-  🤗 <a href="https://huggingface.co/nex-agi/Nex-N2.5-Pro">Hugging Face</a>&nbsp; · &nbsp;
   🌐 <a href="https://nex-agi.com/">Website</a>&nbsp; · &nbsp;
   🔀 <a href="https://openrouter.ai/nex-agi/nex-n2.5-pro">OpenRouter (Pro)</a>
 </p>
@@ -46,7 +46,7 @@ Model weights for the Nex-N2.5 family will be released as open source, alongside
 - **Nex-N2.5-Pro:** [Hugging Face](https://huggingface.co/nex-agi/Nex-N2.5-Pro) | [ModelScope](https://modelscope.cn/models/nex-agi/Nex-N2.5-Pro)
 - **Nex-N2.5-mini:** [Hugging Face](https://huggingface.co/nex-agi/Nex-N2.5-mini) | [ModelScope](https://modelscope.cn/models/nex-agi/Nex-N2.5-mini)
 - **Hosted Access:** [OpenRouter (Nex-N2.5-Pro)](https://openrouter.ai/nex-agi/nex-n2.5-pro)
-- **Websites:** [Global](https://nex-agi.com/) | [China](https://nex-agi.cn/)
 We welcome developers and enterprises to integrate and try Nex-N2.5 and share their feedback.
@@ -258,3 +258,23 @@ Nex-series models emit explicit reasoning traces. Add the `--reasoning-parser qw
 ```bash
 python -m sglang.launch_server --model-path /path/to/your/model --tool-call-parser qwen3_coder --reasoning-parser qwen3
 ```

 <div align="center">
 <p>
   💻 <a href="https://github.com/nex-agi/Nex-N2.5">GitHub</a>&nbsp; · &nbsp;
+  🤗 <a href="https://huggingface.co/collections/nex-agi/nex-n25">Hugging Face</a>&nbsp; · &nbsp;
   🌐 <a href="https://nex-agi.com/">Website</a>&nbsp; · &nbsp;
   🔀 <a href="https://openrouter.ai/nex-agi/nex-n2.5-pro">OpenRouter (Pro)</a>
 </p>
 - **Nex-N2.5-Pro:** [Hugging Face](https://huggingface.co/nex-agi/Nex-N2.5-Pro) | [ModelScope](https://modelscope.cn/models/nex-agi/Nex-N2.5-Pro)
 - **Nex-N2.5-mini:** [Hugging Face](https://huggingface.co/nex-agi/Nex-N2.5-mini) | [ModelScope](https://modelscope.cn/models/nex-agi/Nex-N2.5-mini)
 - **Hosted Access:** [OpenRouter (Nex-N2.5-Pro)](https://openrouter.ai/nex-agi/nex-n2.5-pro)
+- **Websites:** [Global](https://nex-agi.com/)
 We welcome developers and enterprises to integrate and try Nex-N2.5 and share their feedback.
 ```bash
 python -m sglang.launch_server --model-path /path/to/your/model --tool-call-parser qwen3_coder --reasoning-parser qwen3
 ```
+### Thinking Control
+Nex-N2.5 models support three thinking modes, selected per request with the OpenAI-compatible `reasoning_effort` field:
+| `reasoning_effort` | Mode | Behavior |
+|---|---|---|
+| `"none"` | Thinking off | The model answers directly, without a reasoning trace. |
+| `"medium"` (default) | Adaptive thinking | The model decides per request whether, and how much, to reason. |
+| `"high"` | Thinking on | The model always produces a full reasoning trace before answering. |
+```bash
+curl http://localhost:30000/v1/chat/completions \
+  -H "Content-Type: application/json" \
+  -d '{
+    "model": "nex-agi/Nex-N2.5-Pro",
+    "messages": [{"role": "user", "content": "How many prime numbers are there below 100?"}],
+    "reasoning_effort": "high"
+  }'
+```