Update README.md

README.md

@@ -1,5 +1,9 @@
 ---
+inference: false
 license: mit
+tags:
+- Zero-Shot Classification
+pipeline_tag: zero-shot-classification
 ---
 # Zero-shot text classification (model based on albert-xxlarge-v2) trained with self-supervised tuning
 
@@ -26,7 +30,8 @@ There are three versions of models released. The details are:
 | Model | Backbone | #params | accuracy | Speed | #Training data
 |------------|-----------|----------|-------|-------|----|
 |   [zero-shot-classify-SSTuning-base](https://huggingface.co/DAMO-NLP-SG/zero-shot-classify-SSTuning-base)    |  [roberta-base](https://huggingface.co/roberta-base)      |  125M    |  Low    |  High    | 20.48M |  
-|   [zero-shot-classify-SSTuning-large](https://huggingface.co/DAMO-NLP-SG/zero-shot-classify-SSTuning-large)    |    [roberta-large](https://huggingface.co/roberta-large)      | 355M     |   Medium   | Medium | 5.12M |
+|   [zero-shot-classify-SSTuning-large](https://huggingface.co/DAMO-NLP-SG/zero-shot-classify-SSTuning-large)    |    [roberta-large](
+https://huggingface.co/roberta-large)      | 355M     |   Medium   | Medium | 5.12M |
 |   [zero-shot-classify-SSTuning-ALBERT](https://huggingface.co/DAMO-NLP-SG/zero-shot-classify-SSTuning-ALBERT)   |  [albert-xxlarge-v2](https://huggingface.co/albert-xxlarge-v2)      |  235M   |    High  | Low| 5.12M |
 
 Please note that zero-shot-classify-SSTuning-base is trained with more data (20.48M) than the paper, as this will increase the accuracy.