Open galaxyentity904 opened 3 years ago
The code should look something like this instead
# 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 200 tokens,
chat_history_ids = model.generate(
bot_input_ids, max_length=200,
pad_token_id=tokenizer.eos_token_id,
no_repeat_ngram_size=1,
do_sample=True,
top_k=100,
top_p=0.8,
temperature=0.8
)
# pretty print last ouput tokens from bot
print("{}".format(tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)))
Notice the fact that step
is defined in the declaration of the for loop.
I have tried to implement DialoGPT using this code
which is the code given in huggingface. The problem is when I try to generate something there is never a response. To fix this I have used this code I modified to work
My concern is this may not retain past tokens when generating, and when I try to do that it gives me an error that chat_history_ids was never declared before bot_input_ids which needs chat_history_ids to include history. How can I fix this?