Update README.md

README.md

@@ -8,7 +8,7 @@ datasets:
 This is a fine-tuned version of the GPT2 model. It's best suited for text-generation.
 
 ## Model Description
-gpt2-finetuned-ko was fine tuned on the [banking77](https://huggingface.co/datasets/banking77) dataset, which is "composed of online banking queries annotated with their corresponding intents."
+Kwaku/gpt2-finetuned-banking77 was fine tuned on the [banking77](https://huggingface.co/datasets/banking77) dataset, which is "composed of online banking queries annotated with their corresponding intents."
 
 ## Intended Uses and Limitations
 Given the magnitude of the [Microsoft DialoGPT-large](https://huggingface.co/microsoft/DialoGPT-large) model, the author resorted to fine-tuning the gpt2 model for the creation of a chatbot. The intent was for the chatbot to emulate a banking customer agent, hence the use of the banking77 dataset. However, when the fine-tuned model was deployed in the chatbot, the results were undesirable. Its responses were inappropriate and unnecessarily long. The last word of its response is repeated numerously, a major glitch in it. The model performs better in text-generation but is prone to generating banking-related text because of the corpus it was trained on. 
@@ -20,7 +20,7 @@ You can use this model directly with a pipeline for text generation:
 ```python
 >>>from transformers import pipeline
 
->>> model_name = "Kwaku/gpt2-finetuned-ko"
+>>> model_name = "Kwaku/gpt2-finetuned-banking77"
 >>> generator = pipeline("text-generation", model=model_name)
 >>> result = generator("My money is", max_length=15, num_return_sequences=2)
 >>> print(result)