Instructions to use vngrs-ai/Kumru-2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use vngrs-ai/Kumru-2B with Transformers:

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

pipe = pipeline("text-generation", model="vngrs-ai/Kumru-2B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("vngrs-ai/Kumru-2B")
model = AutoModelForCausalLM.from_pretrained("vngrs-ai/Kumru-2B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.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(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use vngrs-ai/Kumru-2B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "vngrs-ai/Kumru-2B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "vngrs-ai/Kumru-2B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/vngrs-ai/Kumru-2B

SGLang

How to use vngrs-ai/Kumru-2B 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 "vngrs-ai/Kumru-2B" \
    --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": "vngrs-ai/Kumru-2B",
		"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 "vngrs-ai/Kumru-2B" \
        --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": "vngrs-ai/Kumru-2B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use vngrs-ai/Kumru-2B with Docker Model Runner:
```
docker model run hf.co/vngrs-ai/Kumru-2B
```

7.4B Model Hakkında

by Q-bert - opened Oct 12, 2025

Discussion

Q-bert

Oct 12, 2025

Merhabalar, öncelikle çalışmalarınız için tebrik ederim. Türkçe için gerçekten güzel bir atılım olmuş. Şu anda kumru.ai üzerinde hostlanan 7.4B modelin Hugging Face üzerinde de yayınlanıp yayınlanmayacağını merak ediyorum.

Q-bert

Oct 12, 2025

Ayrıca gizli değilse, modeli ne kadar büyük bir sunucuda hostladığınızı da merak ediyorum. Bugün oldukça fazla kişinin query gönderdiğini tahmin ediyorum. Kaç bitlik bir inference gerçekleştiriyorsunuz?

Q-bert changed discussion status to closed Oct 13, 2025

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