Summarization
Transformers
PyTorch
Indonesian
encoder-decoder
text2text-generation
pipeline:summarization
bert2gpt
Instructions to use cahya/bert2gpt-indonesian-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cahya/bert2gpt-indonesian-summarization 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="cahya/bert2gpt-indonesian-summarization")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("cahya/bert2gpt-indonesian-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("cahya/bert2gpt-indonesian-summarization") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eee5db6be28fe845ad906acd2cb2063c244608329c8060d74a15e8edf748d28d
- Size of remote file:
- 1.08 GB
- SHA256:
- 3a8a5e8b8a4539592118c54b98a45e63e47dc9578915f9873dd36ef457922774
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