IDEA-CCNL
/

Taiyi-CLIP-Roberta-102M-Chinese

Feature Extraction

text-classification

Inference Endpoints

Model card Files Files and versions Community

weifeng chen commited on Jul 9, 2022

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84e65f5

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1 Parent(s): 5b66f25

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@@ -31,8 +31,8 @@ from transformers import BertForSequenceClassification, BertConfig, BertTokenize
 import numpy as np
 # 加载TaiYi 中文 text encoder
-text_tokenizer = BertTokenizer.from_pretrained("wf-genius/TaiYi-CLIP-ViT-B-32-Roberta-Chinese")
-text_encoder = BertForSequenceClassification.from_pretrained("wf-genius/TaiYi-CLIP-ViT-B-32-Roberta-Chinese").eval()
 text = text_tokenizer(["一只猫", "一只狗",'两只猫', '两只老虎','一只老虎'], return_tensors='pt', padding=True)['input_ids']
 # 加载CLIP的image encoder

 import numpy as np
 # 加载TaiYi 中文 text encoder
+text_tokenizer = BertTokenizer.from_pretrained("IDEA-CCNL/TaiYi-CLIP-Roberta-Chinese")
+text_encoder = BertForSequenceClassification.from_pretrained("IDEA-CCNL/TaiYi-CLIP-Roberta-Chinese").eval()
 text = text_tokenizer(["一只猫", "一只狗",'两只猫', '两只老虎','一只老虎'], return_tensors='pt', padding=True)['input_ids']
 # 加载CLIP的image encoder