Instructions to use jaehyeokdoo2/GRPO_test_e1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use jaehyeokdoo2/GRPO_test_e1 with Transformers:

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

pipe = pipeline("text-generation", model="jaehyeokdoo2/GRPO_test_e1")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("jaehyeokdoo2/GRPO_test_e1")
model = AutoModelForCausalLM.from_pretrained("jaehyeokdoo2/GRPO_test_e1")
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 jaehyeokdoo2/GRPO_test_e1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "jaehyeokdoo2/GRPO_test_e1"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "jaehyeokdoo2/GRPO_test_e1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/jaehyeokdoo2/GRPO_test_e1

SGLang

How to use jaehyeokdoo2/GRPO_test_e1 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 "jaehyeokdoo2/GRPO_test_e1" \
    --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": "jaehyeokdoo2/GRPO_test_e1",
		"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 "jaehyeokdoo2/GRPO_test_e1" \
        --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": "jaehyeokdoo2/GRPO_test_e1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use jaehyeokdoo2/GRPO_test_e1 with Docker Model Runner:
```
docker model run hf.co/jaehyeokdoo2/GRPO_test_e1
```

GRPO_test_e1

Commit History

Upload tokenizer

20caf8c
verified

JaeHyeok Doo commited on Apr 4, 2025

Upload Qwen2ForCausalLM

e469d23
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JaeHyeok Doo commited on Apr 4, 2025

initial commit

2494683
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JaeHyeok Doo commited on Apr 4, 2025

Commit History

Upload tokenizer 20caf8c verified

Upload Qwen2ForCausalLM e469d23 verified

initial commit 2494683 verified

Upload tokenizer

20caf8c
verified

Upload Qwen2ForCausalLM

e469d23
verified

initial commit

2494683
verified