Instructions to use opencsg/Agentic-27B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use opencsg/Agentic-27B with Transformers:

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

pipe = pipeline("image-text-to-text", model="opencsg/Agentic-27B")
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)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("opencsg/Agentic-27B")
model = AutoModelForMultimodalLM.from_pretrained("opencsg/Agentic-27B", 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=256)
print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use opencsg/Agentic-27B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "opencsg/Agentic-27B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "opencsg/Agentic-27B",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/opencsg/Agentic-27B

SGLang

How to use opencsg/Agentic-27B 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 "opencsg/Agentic-27B" \
    --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": "opencsg/Agentic-27B",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

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 "opencsg/Agentic-27B" \
        --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": "opencsg/Agentic-27B",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Docker Model Runner
How to use opencsg/Agentic-27B with Docker Model Runner:
```
docker model run hf.co/opencsg/Agentic-27B
```

ZionWong commited on Sep 15

Commit

45fc7da

verified ·

1 Parent(s): ac231a4

Update README.md

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README.md +5 -3

README.md CHANGED Viewed

@@ -4,7 +4,7 @@ language:
 - en
 license: other
 library_name: transformers
-pipeline_tag: image-text-to-text
 base_model:
 - Qwen/Qwen3.8-27B
 tags:
@@ -161,7 +161,8 @@ vllm serve OpenCSG/Agentic-27B \
   --enable-prefix-caching \
   --enable-auto-tool-choice \
   --tool-call-parser qwen3_xml \
-  --enforce-eager
 ```
 ```python
@@ -330,7 +331,8 @@ vllm serve OpenCSG/Agentic-27B \
   --enable-prefix-caching \
   --enable-auto-tool-choice \
   --tool-call-parser qwen3_xml \
-  --enforce-eager
 ```
 ```python

 - en
 license: other
 library_name: transformers
+pipeline_tag: text_generation
 base_model:
 - Qwen/Qwen3.8-27B
 tags:
   --enable-prefix-caching \
   --enable-auto-tool-choice \
   --tool-call-parser qwen3_xml \
+  --reasoning-parser qwen3 \
+  --generation-config vllm
 ```
 ```python
   --enable-prefix-caching \
   --enable-auto-tool-choice \
   --tool-call-parser qwen3_xml \
+  --reasoning-parser qwen3 \
+  --generation-config vllm
 ```
 ```python