Resolve all the old dataset link with the new link

app.py

@@ -5,7 +5,7 @@ from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM
 # initialize the environment
 model_name = 'anugrahap/gpt2-indo-textgen'
 HF_TOKEN = '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'
-hf_writer = gr.HuggingFaceDatasetSaver(HF_TOKEN, "gpt2-indo-textgen")
+hf_writer = gr.HuggingFaceDatasetSaver(HF_TOKEN, "gpt2-output")
 
 # define the tokenization method
 tokenizer = AutoTokenizer.from_pretrained(model_name,
@@ -116,7 +116,7 @@ description = "<p><i>This project is a part of thesis requirement of Anugrah Akb
 article = """<p style='text-align: center'>
     <a href='https://huggingface.co/anugrahap/gpt2-indo-textgen' target='_blank'>Link to the Trained Model<b>&nbsp;|</b></a>
     <a href='https://huggingface.co/spaces/anugrahap/gpt2-indo-text-gen/tree/main' target='_blank'>Link to the Project Repository<b>&nbsp;|</b></a>
-    <a href='https://huggingface.co/datasets/anugrahap/gpt2-indo-textgen/' target='_blank'>Link to the Autosaved Generated Output<b>&nbsp;|</b></a>
+    <a href='https://huggingface.co/datasets/anugrahap/gpt2-output/' target='_blank'>Link to the Autosaved Generated Output<b>&nbsp;|</b></a>
     <a href='https://d4mucfpksywv.cloudfront.net/better-language-models/language_models_are_unsupervised_multitask_learners.pdf' target='_blank'>Original Paper</a><br></p>
     <p style='text-align: center'> Trained on Indo4B Benchmark Dataset of Indonesian language Wikipedia with a Causal Language Modeling (CLM) objective<br></p>
     <p style='text-align: center'>Copyright Anugrah Akbar Praramadhan 2023</p>