Instructions to use Jeethu/Qwen2.5-14B-Instruct-PLLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Jeethu/Qwen2.5-14B-Instruct-PLLM with MLC-LLM:

# No code snippets available yet for this library.

# To use this model, check the repository files and the library's documentation.

# Want to help? PRs adding snippets are welcome at:
# https://github.com/huggingface/huggingface.js

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Jeethu/Qwen2.5-14B-Instruct-PLLM with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Jeethu/Qwen2.5-14B-Instruct-PLLM"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Jeethu/Qwen2.5-14B-Instruct-PLLM",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Jeethu/Qwen2.5-14B-Instruct-PLLM

SGLang

How to use Jeethu/Qwen2.5-14B-Instruct-PLLM 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 "Jeethu/Qwen2.5-14B-Instruct-PLLM" \
    --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": "Jeethu/Qwen2.5-14B-Instruct-PLLM",
		"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 "Jeethu/Qwen2.5-14B-Instruct-PLLM" \
        --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": "Jeethu/Qwen2.5-14B-Instruct-PLLM",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Jeethu/Qwen2.5-14B-Instruct-PLLM with Docker Model Runner:
```
docker model run hf.co/Jeethu/Qwen2.5-14B-Instruct-PLLM
```

4-bit GPTQ quantized version of Qwen2.5-14B-Instruct.

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Model tree for Jeethu/Qwen2.5-14B-Instruct-PLLM

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Qwen/Qwen2.5-14B

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