Create README.md

README.md

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+---
+language: eng
+datasets:
+- banking77
+---
+
+# GPT2 Fine-tuned KO
+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."
+
+## Intended Uses and Limitations
+Given the hugeness 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, unnecessarily long and repetitive. The model performs better in text-generation but is prone to generate baking-related texted because of the corpus it was trained on. 
+
+### How to use
+
+You can use this model directly with a pipeline for text generation:
+
+```python
+>>>from transformers import pipeline
+
+>>> model_name = "Kwaku/gpt2-finetuned-ko"
+>>> generator = pipeline("text-generation", model=model_name)
+>>> result = generator("My money is", max_length=15, num_return_sequences=2)
+>>> print(result)
+
+[{'generated_text': 'My money is stuck in ATM pending. Please cancel this transaction and refund it'}, {'generated_text': 'My money is missing. How do I get a second card, and how'}]
+```
+
+### Limitations and bias
+
+For users who want a diverse text-generator, this model's tendency to generate mostly bank-related text will be a drawback. It also inherits [the biases of its parent model, the GPT2](https://huggingface.co/gpt2#limitations-and-bias).