| | --- |
| | tags: |
| | - conversational |
| | --- |
| | |
| | # My Awesome Model |
| |
|
| | from transformers import AutoTokenizer, AutoModelWithLMHead |
| |
|
| | tokenizer = AutoTokenizer.from_pretrained("r3dhummingbird/DialoGPT-medium-joshua") |
| | |
| | model = AutoModelWithLMHead.from_pretrained("r3dhummingbird/DialoGPT-medium-joshua") |
| |
|
| | # 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("JoshuaBot: {}".format(tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True))) |
| | |
| | |