Summarization
Transformers
PyTorch
Indonesian
encoder-decoder
text2text-generation
pipeline:summarization
bert2bert
Instructions to use cahya/bert2bert-indonesian-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cahya/bert2bert-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/bert2bert-indonesian-summarization")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("cahya/bert2bert-indonesian-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("cahya/bert2bert-indonesian-summarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
updated the generator to use temperature and sample
2be9212 -
updated the readme
e346883
-
trained another 12 epochs
Cahya Wirawan10b22bf
-
fixecd the tokenizers and vocab file
Cahya Wirawan163eb96
-
updated the model (it. 36000)
ab29c90
-
update readme
75ddf9d -
added README.md
f184de0 -
added bert2bert model (it. 7500)
c85d691 -
initial commit
9130709