Instructions to use DFveloper/AIKAR-3-Pro-unquantized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use DFveloper/AIKAR-3-Pro-unquantized with Transformers:

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

pipe = pipeline("image-text-to-text", model="DFveloper/AIKAR-3-Pro-unquantized")
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("DFveloper/AIKAR-3-Pro-unquantized")
model = AutoModelForMultimodalLM.from_pretrained("DFveloper/AIKAR-3-Pro-unquantized")
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 DFveloper/AIKAR-3-Pro-unquantized with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "DFveloper/AIKAR-3-Pro-unquantized"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "DFveloper/AIKAR-3-Pro-unquantized",
		"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/DFveloper/AIKAR-3-Pro-unquantized

SGLang

How to use DFveloper/AIKAR-3-Pro-unquantized 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 "DFveloper/AIKAR-3-Pro-unquantized" \
    --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": "DFveloper/AIKAR-3-Pro-unquantized",
		"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 "DFveloper/AIKAR-3-Pro-unquantized" \
        --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": "DFveloper/AIKAR-3-Pro-unquantized",
		"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 DFveloper/AIKAR-3-Pro-unquantized with Docker Model Runner:
```
docker model run hf.co/DFveloper/AIKAR-3-Pro-unquantized
```

DFveloper commited on 3 days ago

Commit

9f79749

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1 Parent(s): 7e3051d

Update README.md

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README.md CHANGED Viewed

@@ -45,7 +45,7 @@ AIKAR 3 Pro는 다음 세 가지 단계를 거쳐 완성되었습니다:
 ```python
 from transformers import AutoModelForCausalLM, AutoTokenizer
-model_id = "AIKAR/AIKAR-3-pro-26b"
 tokenizer = AutoTokenizer.from_pretrained(model_id)
 model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto", torch_dtype="auto")
@@ -68,4 +68,4 @@ AIKAR 3 Pro는 추론 능력을 강화한 모델입니다. 따라서 답을 바
 - **Report issues:** [Github Issue Link]
 ---
-*© 2024 LOOP AIKAR Laboratory. All Rights Reserved.*

 ```python
 from transformers import AutoModelForCausalLM, AutoTokenizer
+model_id = "DFveloper/AIKAR-3-Pro-unquantized"
 tokenizer = AutoTokenizer.from_pretrained(model_id)
 model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto", torch_dtype="auto")
 - **Report issues:** [Github Issue Link]
 ---
+*© 2026 LOOP AIKAR Laboratory. All Rights Reserved.*