Instructions to use NLPBada/kobart-chat-persona-extraction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NLPBada/kobart-chat-persona-extraction 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="NLPBada/kobart-chat-persona-extraction")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("NLPBada/kobart-chat-persona-extraction") model = AutoModelForSeq2SeqLM.from_pretrained("NLPBada/kobart-chat-persona-extraction") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ec04cc5eeeea29e39250bc83701d7b68789bbd07fd3dda2e22d202cd54acb3f0
- Size of remote file:
- 496 MB
- SHA256:
- 64491b7241168aa0d30278024dc62d646aa8e6a489f53529c537f47d22b1b73e
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