Instructions to use jaehyeokdoo2/GRPO_test_e5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use jaehyeokdoo2/GRPO_test_e5 with Transformers:

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

pipe = pipeline("text-generation", model="jaehyeokdoo2/GRPO_test_e5")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("jaehyeokdoo2/GRPO_test_e5")
model = AutoModelForCausalLM.from_pretrained("jaehyeokdoo2/GRPO_test_e5")
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_e5 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "jaehyeokdoo2/GRPO_test_e5"
# 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_e5",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/jaehyeokdoo2/GRPO_test_e5

SGLang

How to use jaehyeokdoo2/GRPO_test_e5 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_e5" \
    --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_e5",
		"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_e5" \
        --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_e5",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use jaehyeokdoo2/GRPO_test_e5 with Docker Model Runner:
```
docker model run hf.co/jaehyeokdoo2/GRPO_test_e5
```

GRPO_test_e5

Commit History

Upload tokenizer

ab07b48
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JaeHyeok Doo commited on Apr 4, 2025

Upload Qwen2ForCausalLM

c1fec45
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JaeHyeok Doo commited on Apr 4, 2025

initial commit

a8de53f
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JaeHyeok Doo commited on Apr 4, 2025

Commit History

Upload tokenizer ab07b48 verified

Upload Qwen2ForCausalLM c1fec45 verified

initial commit a8de53f verified

Upload tokenizer

ab07b48
verified

Upload Qwen2ForCausalLM

c1fec45
verified

initial commit

a8de53f
verified