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nytestalkerq/DialoGPT-medium-joshua
DialoGPT-medium-joshua is a text generation model from nytestalkerq. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as mit.
This is an instance of microsoft/DialoGPT-medium trained on a game character, Joshua from The World Ends With You. The data comes from a Kaggle game script dataset.
Downloads · 30 days
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From the Hugging Face model README
This is an instance of microsoft/DialoGPT-medium trained on a game character, Joshua from The World Ends With You. The data comes from a Kaggle game script dataset. Chat with the 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)))