model update

README.md

@@ -5,7 +5,7 @@ metrics:
 - f1
 - accuracy
 model-index:
-- name: roberta-base-tweet-topic-single-all
+- name: cardiffnlp/roberta-base-tweet-topic-single-all
   results:
   - task:
       type: text-classification
@@ -32,7 +32,7 @@ widget:
 - text: "Love to take night time bike rides at the jersey shore. Seaside Heights boardwalk. Beautiful weather. Wishing everyone a safe Labor Day weekend in the US." 
   example_title: "Example 2"
 ---
-# roberta-base-tweet-topic-single-all
+# cardiffnlp/roberta-base-tweet-topic-single-all
 
 This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the [tweet_topic_single](https://huggingface.co/datasets/cardiffnlp/tweet_topic_single). This model is fine-tuned on `train_all` split and validated on `test_2021` split of tweet_topic.
 Fine-tuning script can be found [here](https://huggingface.co/datasets/cardiffnlp/tweet_topic_single/blob/main/lm_finetuning.py). It achieves the following results on the test_2021 set:
@@ -47,7 +47,7 @@ Fine-tuning script can be found [here](https://huggingface.co/datasets/cardiffnl
 ```python
 from transformers import pipeline
 
-pipe = pipeline("text-classification", "roberta-base-tweet-topic-single-all")  
+pipe = pipeline("text-classification", "cardiffnlp/roberta-base-tweet-topic-single-all")  
 topic = pipe("Love to take night time bike rides at the jersey shore. Seaside Heights boardwalk. Beautiful weather. Wishing everyone a safe Labor Day weekend in the US.")
 print(topic)
 ```