Instructions to use alaggung/bart-rl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alaggung/bart-rl with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("summarization", model="alaggung/bart-rl")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("alaggung/bart-rl") model = AutoModelForSeq2SeqLM.from_pretrained("alaggung/bart-rl") - Notebooks
- Google Colab
- Kaggle
BART R3F
[2021 훈민정음 한국어 음성•자연어 인공지능 경진대회] 대화요약 부문 알라꿍달라꿍 팀의 대화요약 학습 샘플 모델을 공유합니다.
bart-r3f 모델에 2021-dialogue-summary-competition 레포지토리의 RL 기법을 적용해 대화요약 Task를 학습한 모델입니다.
데이터는 AIHub 한국어 대화요약 데이터를 사용하였습니다.
- Downloads last month
- 4