Instructions to use WangYe007/Test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use WangYe007/Test with PEFT:

from peft import PeftModel
from transformers import AutoModelForCausalLM

base_model = AutoModelForCausalLM.from_pretrained("OneThink/OneThinker-8B")
model = PeftModel.from_pretrained(base_model, "WangYe007/Test")

Transformers

How to use WangYe007/Test with Transformers:

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

pipe = pipeline("text-generation", model="WangYe007/Test")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("WangYe007/Test", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use WangYe007/Test with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "WangYe007/Test"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "WangYe007/Test",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/WangYe007/Test

SGLang

How to use WangYe007/Test 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 "WangYe007/Test" \
    --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": "WangYe007/Test",
		"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 "WangYe007/Test" \
        --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": "WangYe007/Test",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use WangYe007/Test with Docker Model Runner:
```
docker model run hf.co/WangYe007/Test
```

Test

8.93 GB

Ctrl+K

1 contributor

History: 5 commits

WangYe007

Upload folder using huggingface_hub

59e5ba2 verified 16 days ago

WangYe007
/

Test

Detected Pickle imports (7)

Detected Pickle imports (7)

Detected Pickle imports (7)

Detected Pickle imports (7)

Detected Pickle imports (7)

Detected Pickle imports (7)

Detected Pickle imports (7)

Detected Pickle imports (7)

Pickle imports

Detected Pickle imports (14)