Instructions to use kakaocorp/kanana-1.5-2.1b-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use kakaocorp/kanana-1.5-2.1b-base with Transformers:

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

pipe = pipeline("text-generation", model="kakaocorp/kanana-1.5-2.1b-base")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("kakaocorp/kanana-1.5-2.1b-base")
model = AutoModelForMultimodalLM.from_pretrained("kakaocorp/kanana-1.5-2.1b-base")
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 Settings

vLLM

How to use kakaocorp/kanana-1.5-2.1b-base with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "kakaocorp/kanana-1.5-2.1b-base"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "kakaocorp/kanana-1.5-2.1b-base",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/kakaocorp/kanana-1.5-2.1b-base

SGLang

How to use kakaocorp/kanana-1.5-2.1b-base 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 "kakaocorp/kanana-1.5-2.1b-base" \
    --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": "kakaocorp/kanana-1.5-2.1b-base",
		"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 "kakaocorp/kanana-1.5-2.1b-base" \
        --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": "kakaocorp/kanana-1.5-2.1b-base",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use kakaocorp/kanana-1.5-2.1b-base with Docker Model Runner:
```
docker model run hf.co/kakaocorp/kanana-1.5-2.1b-base
```

wavy-jung commited on May 22, 2025

Commit

d0af702

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1 Parent(s): c3b118a

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@@ -52,6 +52,13 @@ training_regime: bf16 mixed precision
 `Kanana 1.5`, a newly introduced version of the Kanana model family, presents substantial enhancements in **coding, mathematics, and function calling capabilities** over the previous version, enabling broader application to more complex real-world problems. This new version now can handle __up to 32K tokens length natively and up to 128K tokens using YaRN__, allowing the model to maintain coherence when handling extensive documents or engaging in extended conversations. Furthermore, Kanana 1.5 delivers more natural and accurate conversations through a __refined post-training process__.
 > [!Note]
 > Neither the pre-training nor the post-training data includes Kakao user data.

 `Kanana 1.5`, a newly introduced version of the Kanana model family, presents substantial enhancements in **coding, mathematics, and function calling capabilities** over the previous version, enabling broader application to more complex real-world problems. This new version now can handle __up to 32K tokens length natively and up to 128K tokens using YaRN__, allowing the model to maintain coherence when handling extensive documents or engaging in extended conversations. Furthermore, Kanana 1.5 delivers more natural and accurate conversations through a __refined post-training process__.
+<p align="center">
+<br>
+    <picture>
+        <img src="./assets/performance/kanana-1.5-radar-2.1b.png" width="80%" style="margin: 40px auto;">
+    </picture>
+</br>
 > [!Note]
 > Neither the pre-training nor the post-training data includes Kakao user data.

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