|
|
| import os
|
|
|
| from openai import OpenAI
|
|
|
| os.environ['CUDA_VISIBLE_DEVICES'] = '0'
|
|
|
|
|
| def infer(client, model: str, messages):
|
| resp = client.chat.completions.create(model=model, messages=messages)
|
| classify = resp.choices[0].message.content
|
| print(f'messages: {messages}')
|
| print(f'classify: {classify}')
|
| return classify
|
|
|
|
|
| def run_client(host: str = '127.0.0.1', port: int = 8000):
|
| client = OpenAI(
|
| api_key='EMPTY',
|
| base_url=f'http://{host}:{port}/v1',
|
| )
|
| model = client.models.list().data[0].id
|
| print(f'model: {model}')
|
|
|
| messages = [{
|
| 'role': 'user',
|
| 'content': 'What is the capital of China?',
|
| }, {
|
| 'role': 'assistant',
|
| 'content': 'Beijing',
|
| }]
|
| infer(client, model, messages)
|
|
|
|
|
| if __name__ == '__main__':
|
| from swift import run_deploy, DeployArguments
|
| with run_deploy(
|
| DeployArguments(
|
| model='/your/seq_cls/checkpoint-xxx',
|
| task_type='seq_cls',
|
| infer_backend='vllm',
|
| num_labels=2,
|
| verbose=False,
|
| log_interval=-1)) as port:
|
| run_client(port=port)
|
|
|
