How to use from
vLLM
Install from pip and serve model
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "CHE-72-ZLab/Alibaba-Qwen2-0_5B-Instruct-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "CHE-72-ZLab/Alibaba-Qwen2-0_5B-Instruct-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'
Use Docker
docker model run hf.co/CHE-72-ZLab/Alibaba-Qwen2-0_5B-Instruct-GGUF:
Quick Links

CHE-72-ZLab/Alibaba-Qwen2-0_5B-Instruct-GGUF

This model was converted to GGUF format from Qwen/Qwen2-0.5B-Instruct using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.

Downloads last month
259
GGUF
Model size
0.5B params
Architecture
qwen2
Hardware compatibility
Log In to add your hardware

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

Inference Providers NEW
This model isn't deployed by any Inference Provider. ๐Ÿ™‹ Ask for provider support

Model tree for CHE-72-ZLab/Alibaba-Qwen2-0_5B-Instruct-GGUF

Base model

Qwen/Qwen2-0.5B
Quantized
(91)
this model