HuggingFace already did most of the work for us and added a classification layer to the GPT2 model. In creating the model I usedGPT2ForSequenceClassification. Since we have a custom padding token we need to initialize it for the model usingmodel.config.pad_token_id. Finally we will need t...
从开源角度来说,huggingface的transformers会更好,因为contributors更多,社区更活跃,所以算是入坑了😓 Text-Classification 代码传送门:bert4pl Text-Classification的算法实现比较简单,首先经过bert的encoder之后取output第一维度的值也就是[CLS]的向量,[CLS]代表着这句话的句向量,然后接一个dropout层和一个全...
在https://huggingface.co/spaces/mteb/leaderboard上可以看到,acge模型已经在目前业界最全面、最权威的中文语义向量评测基准C-MTEB(Chinese Massive Text Embedding Benchmark)的榜单中获得了第一名的成绩。 由上表可以看到,acge_text_embedding模型在“Classification Average (9 datasets)”这一列中,acge_text_embeddi...
在https://huggingface.co/spaces/mteb/leaderboard上可以看到,acge模型已经在目前业界最全面、最权威的中文语义向量评测基准C-MTEB(Chinese Massive Text Embedding Benchmark)的榜单中获得了第一名的成绩。 由上表可以看到,acge_text_embedding模型在“Classification Average (9 datasets)”这一列中,acge_text_embeddi...
在https://huggingface.co/spaces/mteb/leaderboard上可以看到,acge模型已经在目前业界最全面、最权威的中文语义向量评测基准C-MTEB(Chinese Massive Text Embedding Benchmark)的榜单中获得了第一名的成绩。 由上表可以看到,acge_text_embedding模型在“Classification Average (9 datasets)”这一列中,acge_text_embeddi...
ORIGINAL ANSWER: The 17th of May, a new pull request https://github.com/huggingface/transformers/pull/3957 with what you are asking for has been merged, therefore now our life is way easier, you can you it in the pipeline like ner = pipeline('ner', grouped_entities=Tr...
But before that I figured I'd try to get a basic toy example working by fine-tuning GPT-2 on a Huggingface dataset. However, modifying the tutorial code (which fine-tunes BERT for text classification, link here) to instead generate text leads to the following error when trainer.tra...
How to Fine Tune BERT for Text Classification using Transformers in Python Learn how to use HuggingFace transformers library to fine tune BERT and other transformer models for text classification task in Python.How to Perform Text Summarization using Transformers in Python Learn how to use Huggingface...
API_URL = "https://datasets-server.huggingface.co/search?dataset=jamescalam/world-cities-geo&config=default&split=train&query=Albania" def query(): response = requests.get(API_URL) return response.json() data = query() ``` - Using [filter](https://huggingface.co/docs/datasets-server/filt...
最近,专注于自然语言处理(NLP)的初创公司 HuggingFace 对其非常受欢迎的 Transformers 库进行了重大更新,从而为 PyTorch 和 Tensorflow 2.0 两大深度学习框架提供了前所未有的兼容性。 03 Python使用神经网络进行简单文本分类 出于演示目的,我们将使用 20个新闻组 数据集。数据分为20个类别,我们的工作是预测这些类别。