kingabzpro's picture
conversational
e4ab0df
---
language: English
datasets:
- Andrada Olteanu Rickmorty-Scripts
tags:
- conversational
- Transformers
- gpt2
- Chatbot
- Rick&Morty
license: apache-2.0
metrics:
- Perplexity
---
# Source Code
[<img src="https://api.flatworld.co/wp-content/uploads/2020/10/DAGsHub-Logo.png" alt="dagshub" width="150"/>](https://dagshub.com/kingabzpro/DailoGPT-RickBot)
[![DAGsHub](https://img.shields.io/badge/github-DailoGPT_RickBot-ffbf00?logo=github&color=black&style=for-the-badge)](https://github.com/kingabzpro/DailoGPT-RickBot)
# Testing
```python
tokenizer = AutoTokenizer.from_pretrained('kingabzpro/DialoGPT-small-Rick-Bot')
model = AutoModelWithLMHead.from_pretrained('kingabzpro/DialoGPT-small-Rick-Bot')
# Let's chat for 4 lines
for step in range(4):
# 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')
# print(new_user_input_ids)
# 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=200,
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
)
# pretty print last ouput tokens from bot
print("RickBot: {}".format(tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)))
```
**Result**
perplexity : 8.53