Instructions to use YeonwooSung/Llama-3.1-8B-OpenO1-SFT-v0.2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use YeonwooSung/Llama-3.1-8B-OpenO1-SFT-v0.2 with Transformers:

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

pipe = pipeline("text-generation", model="YeonwooSung/Llama-3.1-8B-OpenO1-SFT-v0.2")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("YeonwooSung/Llama-3.1-8B-OpenO1-SFT-v0.2")
model = AutoModelForCausalLM.from_pretrained("YeonwooSung/Llama-3.1-8B-OpenO1-SFT-v0.2", device_map="auto")
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 YeonwooSung/Llama-3.1-8B-OpenO1-SFT-v0.2 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "YeonwooSung/Llama-3.1-8B-OpenO1-SFT-v0.2"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "YeonwooSung/Llama-3.1-8B-OpenO1-SFT-v0.2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/YeonwooSung/Llama-3.1-8B-OpenO1-SFT-v0.2

SGLang

How to use YeonwooSung/Llama-3.1-8B-OpenO1-SFT-v0.2 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 "YeonwooSung/Llama-3.1-8B-OpenO1-SFT-v0.2" \
    --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": "YeonwooSung/Llama-3.1-8B-OpenO1-SFT-v0.2",
		"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 "YeonwooSung/Llama-3.1-8B-OpenO1-SFT-v0.2" \
        --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": "YeonwooSung/Llama-3.1-8B-OpenO1-SFT-v0.2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use YeonwooSung/Llama-3.1-8B-OpenO1-SFT-v0.2 with Docker Model Runner:
```
docker model run hf.co/YeonwooSung/Llama-3.1-8B-OpenO1-SFT-v0.2
```

Llama-3.1-8B-OpenO1-SFT-v0.2

Commit History

Update README.md

ac3d309
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Yeonwoo Sung commited on Feb 23, 2025

Update README.md

86528d6
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Yeonwoo Sung commited on Feb 20, 2025

Upload tokenizer

4970cb8
verified

Yeonwoo Sung commited on Feb 19, 2025

Upload LlamaForCausalLM

47c880b
verified

Yeonwoo Sung commited on Feb 19, 2025

initial commit

02c3a43
verified

Yeonwoo Sung commited on Feb 19, 2025

Commit History

Update README.md ac3d309 verified

Update README.md 86528d6 verified

Upload tokenizer 4970cb8 verified

Upload LlamaForCausalLM 47c880b verified

initial commit 02c3a43 verified

Update README.md

ac3d309
verified

Update README.md

86528d6
verified

Upload tokenizer

4970cb8
verified

Upload LlamaForCausalLM

47c880b
verified

initial commit

02c3a43
verified