Instructions to use Trendyol/Trendyol-LLM-Asure-12B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Trendyol/Trendyol-LLM-Asure-12B with Transformers:

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

pipe = pipeline("image-text-to-text", model="Trendyol/Trendyol-LLM-Asure-12B")
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("Trendyol/Trendyol-LLM-Asure-12B")
model = AutoModelForMultimodalLM.from_pretrained("Trendyol/Trendyol-LLM-Asure-12B", 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]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Trendyol/Trendyol-LLM-Asure-12B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Trendyol/Trendyol-LLM-Asure-12B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Trendyol/Trendyol-LLM-Asure-12B",
		"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/Trendyol/Trendyol-LLM-Asure-12B

SGLang

How to use Trendyol/Trendyol-LLM-Asure-12B 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 "Trendyol/Trendyol-LLM-Asure-12B" \
    --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": "Trendyol/Trendyol-LLM-Asure-12B",
		"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 "Trendyol/Trendyol-LLM-Asure-12B" \
        --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": "Trendyol/Trendyol-LLM-Asure-12B",
		"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 Trendyol/Trendyol-LLM-Asure-12B with Docker Model Runner:
```
docker model run hf.co/Trendyol/Trendyol-LLM-Asure-12B
```

What are you guys planning on doing with this model?

by uran1um1 - opened 25 days ago

Discussion

uran1um1

25 days ago

Hello, I think that this is a good idea. Fine tuning an existing model for Turkish language is promising. However, I was wondering if there would be a user side application to this model where users can chat with it.

tolgayan

Trendyol org 25 days ago

Thank you for the kind words and the thoughtful question!

Yes, we are actively exploring user-facing applications where Turkish-capable models can create real value. One of the main directions is conversational shopping assistance: helping users discover products, clarify their intent, ask follow-up questions, and get more relevant recommendations through a natural Turkish dialogue experience.

We are also working on QA assistant experiences, where users can ask product-related questions and receive helpful, context-aware answers based on available product information.

For now, we see this model as an important building block toward more useful, localized, and context-aware assistant experiences. We will continue sharing updates as the work evolves.

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