wehub-resource-sync
36 lines
1.2 KiB
Python
36 lines
1.2 KiB
Python
import os
|
|
from typing import List
|
|
|
|
from swift import BaseArguments, InferRequest, TransformersEngine, get_template
|
|
|
|
os.environ['IMAGE_MAX_TOKEN_NUM'] = '1024'
|
|
os.environ['VIDEO_MAX_TOKEN_NUM'] = '128'
|
|
os.environ['FPS_MAX_FRAMES'] = '16'
|
|
|
|
infer_request = InferRequest(
|
|
messages=[{
|
|
'role':
|
|
'user',
|
|
'content':
|
|
"多标签分类，类别包括：['aeroplane', 'bicycle', 'bird', 'boat', 'bottle', "
|
|
"'bus', 'car', 'cat', 'chair', 'cow', 'diningtable', 'dog', 'horse', "
|
|
"'motorbike', 'person', 'pottedplant', 'sheep', 'sofa', 'train', 'tvmonitor']"
|
|
}],
|
|
images=['xxx.jpg'])
|
|
adapter_path = 'output/vx-xxx/checkpoint-xxx'
|
|
args = BaseArguments.from_pretrained(adapter_path)
|
|
|
|
engine = TransformersEngine(
|
|
args.model,
|
|
adapters=[adapter_path],
|
|
task_type='seq_cls',
|
|
num_labels=args.num_labels,
|
|
problem_type=args.problem_type)
|
|
template = get_template(
|
|
engine.processor, args.system, template_type=args.template, use_chat_template=args.use_chat_template)
|
|
engine.template = template
|
|
|
|
resp_list = engine.infer([infer_request])
|
|
response: List[int] = resp_list[0].choices[0].message.content
|
|
print(f'response: {response}')
|