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@@ -33,19 +33,19 @@ This modelcard aims to be a base template for new models. It has been generated
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  ## Uses
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- from transformers import AutoModelForCausalLM, AutoTokenizer
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- import torch
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- tokenizer = AutoTokenizer.from_pretrained("finex/Stage-IOTGraphic")
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- model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-medium")
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- # Let's chat for 5 lines
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- #for step in range(5):
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  # encode the new user input, add the eos_token and return a tensor in Pytorch
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  new_user_input_ids = tokenizer.encode(input(">> User:") + tokenizer.eos_token, return_tensors='pt')
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- # append the new user input tokens to the chat history
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  bot_input_ids = torch.cat([chat_history_ids, new_user_input_ids], dim=-1) if step > 0 else new_user_input_ids
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  # generated a response while limiting the total chat history to 1000 tokens,
 
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  ## Uses
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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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+ import torch
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+ tokenizer = AutoTokenizer.from_pretrained("finex/Stage-IOTGraphic")
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+ model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-medium")
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+ Let's chat for 5 lines
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+ for step in range(5):
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  # encode the new user input, add the eos_token and return a tensor in Pytorch
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  new_user_input_ids = tokenizer.encode(input(">> User:") + tokenizer.eos_token, return_tensors='pt')
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+ append the new user input tokens to the chat history
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  bot_input_ids = torch.cat([chat_history_ids, new_user_input_ids], dim=-1) if step > 0 else new_user_input_ids
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  # generated a response while limiting the total chat history to 1000 tokens,