Instructions to use OLAIR/ko-r1-1.5b-preview with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use OLAIR/ko-r1-1.5b-preview with Transformers:

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

pipe = pipeline("text-generation", model="OLAIR/ko-r1-1.5b-preview")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("OLAIR/ko-r1-1.5b-preview")
model = AutoModelForMultimodalLM.from_pretrained("OLAIR/ko-r1-1.5b-preview")
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 OLAIR/ko-r1-1.5b-preview with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "OLAIR/ko-r1-1.5b-preview"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "OLAIR/ko-r1-1.5b-preview",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/OLAIR/ko-r1-1.5b-preview

SGLang

How to use OLAIR/ko-r1-1.5b-preview 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 "OLAIR/ko-r1-1.5b-preview" \
    --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": "OLAIR/ko-r1-1.5b-preview",
		"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 "OLAIR/ko-r1-1.5b-preview" \
        --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": "OLAIR/ko-r1-1.5b-preview",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use OLAIR/ko-r1-1.5b-preview with Docker Model Runner:
```
docker model run hf.co/OLAIR/ko-r1-1.5b-preview
```

Can't work with GPU Interface in HF Interface Endpoints?

by hmmhmmhm - opened Jan 29, 2025

Discussion

hmmhmmhm

Jan 29, 2025

Hello I have tried to run that model with Nvidia T4 GPU 16GB instances. However, I get an error like the log below. Is there a minimum GPU specification that would be recommended?

[Deploy Log]
https://gist.github.com/hmmhmmhm/f5190514c99ae1edc35edc009b39f435

hmmhmmhm

Jan 29, 2025

I just successfully ran that model with CPUs, the specs used in the deployment are Intel Sapphire Rapids - 16x vCPUs - 32 GB.

hmmhmmhm changed discussion title from Can't work with Hugging Interface Endpoints? to Can't work with GPU Interface in HF Interface Endpoints? Jan 29, 2025

amphora

OLA-AI-Research org Jan 30, 2025

thanks for your interest in cases of hardware constraints you may also try out the model here

https://kor1preview.streamlit.app/

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