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README.md

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+---
+thumbnail: https://huggingface.co/front/thumbnails/dialogpt.png
+language:
+- en
+license: cc-by-4.0
+tags:
+- conversational
+- transformers
+datasets:
+- AfriWOZ
+metrics:
+- perplexity
+widget:
+- text: "How I fit chop for here?"
+---
+
+## DialoGPT_AfriWOZ
+This is a fine-tuned model of DialoGPT (small) on the AfriWOZ dataset. It is intended to be used as a conversational system in Nigeria Pidgin English language.
+The dataset it's trained on is limited in scope, as it covers only certain domains such as restaurants, hotel, taxi, and booking.
+The perplexity achieved on the validation set  38.52.
+* Generation example from an interactive environment:
+|Role | Response |
+|---------|------------|
+|User | I hear say restaurant dey here. |
+|Bot |  |
+|User | Abeg you fit tell me which kind chop dey? |
+|Bot |  |
+|User | You do well. Thank you. |
+|Bot | |
+Please find the information about preprocessing, training and full details of the DialoGPT in the [original DialoGPT repository](https://github.com/microsoft/DialoGPT)
+The paper for this work can be found on arXiv: [https://arxiv.org/pdf/2204.08083.pdf](https://arxiv.org/pdf/2204.08083.pdf)
+### How to use
+Now we are ready to try out how the model works as a chatting partner!
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+tokenizer = AutoTokenizer.from_pretrained("tosin/dialogpt_afriwoz_pidgin")
+model = AutoModelForCausalLM.from_pretrained("tosin/dialogpt_afriwoz_pidgin")
+# 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)
+	# pretty print last ouput tokens from bot
+	print("DialoGPT_pidgin_Bot: {}".format(tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)))
+