t5-large-korean-text-summary
This model is a fine-tuning of paust/pko-t5-large model using AIHUB "summary and report generation data". This model provides a short summary of long sentences in Korean.
μ΄ λͺ¨λΈμ paust/pko-t5-large modelμ AIHUB "μμ½λ¬Έ λ° λ ν¬νΈ μμ± λ°μ΄ν°"λ₯Ό μ΄μ©νμ¬ fine tunning ν κ²μ λλ€. μ΄ λͺ¨λΈμ νκΈλ‘λ μ₯λ¬Έμ μ§§κ² μμ½ν΄ μ€λλ€.
Usage
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
import nltk
nltk.download('punkt')
model_dir = "lcw99/t5-large-korean-text-summary"
tokenizer = AutoTokenizer.from_pretrained(model_dir)
model = AutoModelForSeq2SeqLM.from_pretrained(model_dir)
max_input_length = 512 + 256
text = """
μ£ΌμΈκ³΅ κ°μΈκ΅¬(νμ μ°)λ βμ리λ¨μμ νμ΄κ° λ§μ΄ λλλ° λ€ κ°λ€λ²λ¦°λ€βλ μΉκ΅¬
λ°μμ(νλ΄μ)μ μκΈ°λ₯Ό λ£κ³ μ리λ¨μ° νμ΄λ₯Ό νκ΅μ μμΆνκΈ° μν΄ μ리λ¨μΌλ‘ κ°λ€.
κ΅λ¦½μμ°κ³Όνμ μΈ‘μ βμ€μ λ‘ λ¨λμμμ νμ΄κ° λ§μ΄ μ΄κ³ μλ₯΄ν¨ν°λλ₯Ό λΉλ‘―ν λ¨λ―Έ κ΅κ°μμ νμ΄κ° λ§μ΄ μ‘νλ€βλ©°
βμλ¦¬λ¨ μ°μμλ νμ΄κ° λ§μ΄ μμν κ²βμ΄λΌκ³ μ€λͺ
νλ€.
κ·Έλ¬λ κ΄μΈμ²μ λ°λ₯΄λ©΄ νκ΅μ μ리λ¨μ° νμ΄κ° μμ
λ μ μ μλ€.
μΌκ°μμ βλμ λ²κΈ° μν΄ μ리λ¨μ° νμ΄λ₯Ό ꡬνλ¬ κ° μ€μ μ κ°μ°μ±μ΄ λ¨μ΄μ§λ€βλ μ§μ λ νλ€.
λλΌλ§ λ°°κ²½μ΄ λ 2008~2010λ
μλ μ΄λ―Έ κ΅λ΄μ μλ₯΄ν¨ν°λ, μΉ λ , λ―Έκ΅ λ± μλ©λ¦¬μΉ΄μ° νμ΄κ° μμ
λκ³ μμκΈ° λλ¬Έμ΄λ€.
μ€μ μ‘°λ΄ν μ²΄ν¬ μμ μ νμ‘°νλ βνλ ₯μ Kμ¨βλ νμ΄ μ¬μ
μ΄ μλλΌ μ리λ¨μ μ λ°μ© νΉμμ©μ λ΄μ νλ μ¬μ
μ νλ¬ μ리λ¨μ κ°μλ€.
"""
inputs = ["summarize: " + text]
inputs = tokenizer(inputs, max_length=max_input_length, truncation=True, return_tensors="pt")
output = model.generate(**inputs, num_beams=8, do_sample=True, min_length=10, max_length=100)
decoded_output = tokenizer.batch_decode(output, skip_special_tokens=True)[0]
predicted_title = nltk.sent_tokenize(decoded_output.strip())[0]
print(predicted_title)
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- optimizer: None
- training_precision: float16
Training results
Framework versions
- Transformers 4.22.1
- TensorFlow 2.10.0
- Datasets 2.5.1
- Tokenizers 0.12.1
- Downloads last month
- 7,566
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.