task_path:自定义任务路径,默认为 None 。 3. 命名实体识别 最全中文实体标签 精确模式:(默认),基于百度解语,内置91种词性及专名类别标签 In [12] ner = Taskflow("ner") pprint(ner("《孤女》是2010年九州出版社出版的小说,作者是余兼羽")) [2023-06-05 14:21:31,028] [ INFO] - Already cached...
wgethttps://bj.bcebos.com/paddlenlp/taskflow/demo/model_config.json-P/home/aistudio/custom_model 5.2 使用定制化模型 通过task_path指定自定义模型路径一键加载即可frompaddlenlpimportTaskflow my_senta=Taskflow("sentiment_analysis",model="skep_ernie_1.0_large_ch",task_path="/home/aistudio/custom_model...
5.2 使用定制化模型 通过task_path指定自定义模型路径一键加载即可。 frompaddlenlpimportTaskflow my_senta=Taskflow("sentiment_analysis",model="skep_ernie_1.0_large_ch",task_path="/home/aistudio/custom_model") print(my_senta("不错的酒店,服务还可以,下次还会入住的~")) [{‘text’: ‘不错的酒店,...
loadComponentModel(taskFlowPath); ITask task = taskFlowModel.getTask(new TaskFlowBuilder()); ITaskRuntime taskRt = new TaskRuntimeImpl(taskStateStore); taskStepReturn = task.execute(taskRt); 实现NopTaskFlow的第一步也是最重要的一步是定义元模型task.xdef。然后平台就会根据元模型自动推导得到大量...
task_path='checkpoint/model_best',precison='fp32',batch_size=2,use_fast=True)#y_ie = Taskflow("information_extraction", model="uie-tiny", schema=schema,#precison='fp16', batch_size=2)doc_path = image_srcresults = ie({"doc": doc_path})pprint(results) 开始时间:[2022-12-30 20:33...
batch_size:批处理大小,请结合机器情况进行调整,默认为1。 user_dict:用户自定义词典文件,默认为None。 task_path:自定义任务路径,默认为None。命名实体识别 最全中文实体标签 支持两种模式 # 精确模式(默认),基于百度解语,内置91种词性及专名类别标签 >>> from paddlenlp import Taskflow >>> ner = Taskflow...
2.student模型: student模型推理平均时长:47ms task_path="checkpoint/model_best/" # student ie = Taskflow("information_extraction", model="uie-data-distill-gp", use_fast = True,precision='fp32',task_path=task_path)leon-cas added the question label Mar 6, 2023 github-actions bot added th...
TaskFlowModel taskFlowModel = resourceComponentManager.loadComponentModel(taskFlowPath); ITask task = taskFlowModel.getTask(new TaskFlowBuilder()); ITaskRuntime taskRt = new TaskRuntimeImpl(taskStateStore); taskStepReturn = task.execute(taskRt); ...
task: | order.setRealPrice(order.getOriginalPrice() - 20); System.out.println("优惠20元"); - type: "end" 然后通过如下方式调用流程模型 @Test public void testDiscount() FlowEngine flowEngine = FlowEngine.newInstance(); flowEngine.load(Chain.parseByUri("classpath:flow/bookDiscount.yml"));...
python finetune.py --train_data train_data --save_dir ./checkpoint --model uie-base --learning_rate 1e-5 --num_epochs 10 # 使用微调后的模型进行信息抽取 # fine_tuned_ie = Taskflow("information_extraction", schema=schema, task_path="./checkpoint/model_best") # result = fine_tuned_...