트랜스포머 문장 생성하기

!pip install transformers --quiet
!pip install torch --quiet

from transformers import pipeline

generator = pipeline("text-generation", model="distilgpt2")
generator(
    "In this course, we will teach you how to",
    max_length=30,
    num_return_sequences=2,
)

[{'generated_text': 'In this course, we will teach you how to manipulate the world and '
                    'move your mental and physical capabilities to your advantage.'},
 {'generated_text': 'In this course, we will teach you how to become an expert and '
                    'practice realtime, and with a hands on experience on both real '
                    'time and real'}]

pipe = pipeline(model="FacebookAI/roberta-large-mnli")
pipe("This restaurant is awesome")

from transformers import pipeline

generator = pipeline(model="cateto/korean-gpt-neox-125M")
generator("우리나라의 미래는 ")

# Import the transformers library
from transformers import AutoModelForCausalLM, AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained("cateto/korean-gpt-neox-125M")

model = AutoModelForCausalLM.from_pretrained("cateto/korean-gpt-neox-125M")

# Get user input
user_input = "우리는 앞으로 더나은 미래를"

# Encode the prompt using the tokenizer
input_ids = tokenizer.encode(user_input, return_tensors="pt")

# Generate chatbot output using the model
output_ids = model.generate(
    input_ids,
    num_beams=4,
    repetition_penalty=1.5,
    no_repeat_ngram_size=3
)

# Decode chatbot output ids as text
bot_output = tokenizer.decode(output_ids.tolist()[0], skip_special_tokens=True)

# Print chatbot output
print(f"출력 ## ", bot_output)

# 출력 ##  우리는 앞으로 더나은 미래를 향해 나아갈 수 있다.

from transformers import pipeline
generator = pipeline(model="cateto/korean-gpt-neox-125M")
a = generator("동해물과 백두산이")
b = a[0]['generated_text']
print(b)