## Ko-DialoGPT


### How to use
```python
from transformers import PreTrainedTokenizerFast, GPT2LMHeadModel
import torch


device = 'cuda' if torch.cuda.is_available() else 'cpu'

tokenizer = PreTrainedTokenizerFast.from_pretrained('byeongal/Ko-DialoGPT')
model = GPT2LMHeadModel.from_pretrained('byeongal/Ko-DialoGPT').to(device)

past_user_inputs = []
generated_responses = []

while True:
    user_input = input(">> User:")
    if user_input == 'bye':
        break
    text_idx = tokenizer.encode(user_input + tokenizer.eos_token, return_tensors='pt')
    for i in range(len(generated_responses)-1, len(generated_responses)-3, -1):
        if i < 0:
            break
        encoded_vector = tokenizer.encode(generated_responses[i] + tokenizer.eos_token, return_tensors='pt')
        if text_idx.shape[-1] + encoded_vector.shape[-1] < 1000:
            text_idx = torch.cat([encoded_vector, text_idx], dim=-1)
        else:
            break
        encoded_vector = tokenizer.encode(past_user_inputs[i] + tokenizer.eos_token, return_tensors='pt')
        if text_idx.shape[-1] + encoded_vector.shape[-1] < 1000:
            text_idx = torch.cat([encoded_vector, text_idx], dim=-1)
        else:
            break
    text_idx = text_idx.to(device)
    inference_output = model.generate(
            text_idx,
            max_length=1000,
            num_beams=5,
            top_k=20,
            no_repeat_ngram_size=4,
            length_penalty=0.65,
            repetition_penalty=2.0,
        )
    inference_output = inference_output.tolist()
    bot_response = tokenizer.decode(inference_output[0][text_idx.shape[-1]:], skip_special_tokens=True)
    print(f"Bot: {bot_response}")
    past_user_inputs.append(user_input)
    generated_responses.append(bot_response)
```

### Reference
* [SKT-KoGPT2](https://huggingface.co/skt/kogpt2-base-v2)
* [KETI R&D 데이터](https://aihub.or.kr/opendata/keti-data/recognition-laguage/KETI-02-008)
* [한국어 대화 요약](https://aihub.or.kr/aidata/30714)

{"language": "ko", "license": "cc-by-nc-sa-4.0", "tags": ["gpt2", "conversational"]}
transformers pytorch gpt2 text-generation conversational ko license:cc-by-nc-sa-4.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #gpt2 #text-generation #conversational #ko #license-cc-by-nc-sa-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

## Ko-DialoGPT


### How to use


### Reference
* SKT-KoGPT2
* KETI R&D 데이터
* 한국어 대화 요약

## Ko-DialoGPT ### How to use ### Reference
* SKT-KoGPT2
* KETI R&D 데이터
* 한국어 대화 요약
TAGS
#transformers #pytorch #gpt2 #text-generation #conversational #ko #license-cc-by-nc-sa-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ## Ko-DialoGPT ### How to use ### Reference
* SKT-KoGPT2
* KETI R&D 데이터
* 한국어 대화 요약
passage: TAGS
#transformers #pytorch #gpt2 #text-generation #conversational #ko #license-cc-by-nc-sa-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
## Ko-DialoGPT### How to use### Reference
* SKT-KoGPT2
* KETI R&D 데이터
* 한국어 대화 요약