Instructions to use gogamza/kobart-base-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gogamza/kobart-base-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="gogamza/kobart-base-v1")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("gogamza/kobart-base-v1") model = AutoModel.from_pretrained("gogamza/kobart-base-v1") - Notebooks
- Google Colab
- Kaggle
| language: ko | |
| tags: | |
| - bart | |
| license: mit | |
| ## KoBART-base-v1 | |
| ```python | |
| from transformers import PreTrainedTokenizerFast, BartModel | |
| tokenizer = PreTrainedTokenizerFast.from_pretrained('gogamza/kobart-base-v1') | |
| model = BartModel.from_pretrained('gogamza/kobart-base-v1') | |
| ``` | |