Update README.md

README.md

@@ -5,4 +5,45 @@ language:
 - en
 ---
 
-This literally is the worst model ever :(...
+# HomerBot: A conversational chatbot imitating Homer Simpson
+
+This model is a fine-tuned [DialoGPT](https://huggingface.co/microsoft/DialoGPT-medium) (medium version) on Simpsons [scripts](https://www.kaggle.com/datasets/pierremegret/dialogue-lines-of-the-simpsons).
+
+More specifically, we fine-tune DialoGPT-medium for 3 epochs on 10K **(character utterance, Homer's response)** pairs
+
+For more details, check out our git [repo](https://github.com/jesseDingley/HomerBot) containing all the code.  
+
+### How to use
+
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch 
+
+tokenizer = AutoTokenizer.from_pretrained("DingleyMaillotUrgell/homer-bot")
+model = AutoModelForCausalLM.from_pretrained("DingleyMaillotUrgell/homer-bot")
+
+# Let's chat for 5 lines
+for step in range(5):
+    # encode the new user input, add the eos_token and return a tensor in Pytorch
+    new_user_input_ids = tokenizer.encode(input(">> User: ") + tokenizer.eos_token, return_tensors='pt')
+  
+    # append the new user input tokens to the chat history
+    bot_input_ids = torch.cat([chat_history_ids, new_user_input_ids], dim=-1) if step > 0 else new_user_input_ids
+
+    # generated a response while limiting the total chat history to 1000 tokens, 
+    chat_history_ids = model.generate(
+        bot_input_ids, 
+        max_length=1000,                    
+        pad_token_id=tokenizer.eos_token_id,  
+        no_repeat_ngram_size=3,
+        do_sample=True, 
+        top_k=100, 
+        top_p=0.7,
+        temperature = 0.8
+    )
+    
+    # print last outpput tokens from bot
+    print("Homer: {}".format(tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)))
+```
+