code:https://github.com/IBM/zero-shot-classification-boost-with-self-training 这篇文章出来的时候,ChatGPT 还没火出圈,所以它走的还是传统优化路线。 a. 基座分类模型 文本为 NLI(Natural Language Inference) 式的 zero-shot(推荐 huggingface 的 xlm-roberta-large-xnli,支持中文)。本质上,这是一种迁移学习...
Comprehend-it在各个场景的具体应用请参见huggingface官网,本文仅研究文本分类场景的应用。 文本分类 首先,创建zero-shot-classification pipeline。model除了可以运行时拉去,也可以替换为模型本地路径。 from transformers import pipeline classifier = pipeline("zero-shot-classification", model="knowledgator/comprehend_...
# Create transformer to run a batch job batch_job = huggingface_model_zero_shot.transformer( instance_count=1, instance_type='ml.m5.xlarge', strategy='SingleRecord', assemble_with='Line', output_path=s3_path_join("s3://",sagemaker_config['S3Bucket'],"zero_shot_text_clf", "re...
The Zero-shot Text Classification tool doesn’t require training data and leverages ONNX Runtime using the huggingface transformer model. This tool is part of Alteryx Intelligence Suite. Intelligence Suite requires a separate license and add-on installer to Designer. After you install Designer, ...
Next, we can select this newly-uploaded dataset in the Evaluation on the Hub interface using thetext_zero_shot_classificationtask, select the models we’d like to evaluate, and submit our evaluation jobs! When the job has been completed, you’ll be notified by email that...
Zero Shot Prediction Plugin This plugin allows you to perform zero-shot prediction on your dataset for the following tasks: Image Classification Object Detection Instance Segmentation Semantic Segmentation Given a list of label classes, which you can input either manually, separated by commas, or by ...
Zero-shot learning (ZSL) is a machine learning technique that identifies the target classes without any observed data, using semantic information from some source classes as the basis of knowledge transfer. ZSL has emerged as a new paradigm in machine learning to solve the constraints of classical...
Zero-shot learningin NLP allows a pre-trained LLM to generate responses to tasks that it hasn’t been specifically trained for. In this technique, the model is provided with an input text and a prompt that describes the expected output from the model in natural language. T...
MindNLP对标了HuggingFace,可以更方便地使用fine-tune预训练模型了 5. 未来展望 感觉课程理论部分和代码部分有一点割裂,可以尝试把GPT2的一些新用的技术实现到代码里,使用稍简单点的方式也可以,比如理论讲到的GPT2的两个关键技术,是怎么把prompt的信息融入到训练中的,感觉现在的代码内容没有特别体现出来GPT2的特性,当...
Zero-shot stance detection is pivotal for autonomously discerning user stances on novel emerging topics. This task hinges on effective feature alignment transfer from known to unseen targets. To address this, we introduce a zero-shot stance detection fra