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")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("cahya/bert2bert-indonesian-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("cahya/bert2bert-indonesian-summarization") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- .gitattributes +1 -0
- model.safetensors +3 -0
.gitattributes
CHANGED
|
@@ -6,3 +6,4 @@
|
|
| 6 |
*.tar.gz filter=lfs diff=lfs merge=lfs -text
|
| 7 |
*.ot filter=lfs diff=lfs merge=lfs -text
|
| 8 |
*.onnx filter=lfs diff=lfs merge=lfs -text
|
|
|
|
|
|
| 6 |
*.tar.gz filter=lfs diff=lfs merge=lfs -text
|
| 7 |
*.ot filter=lfs diff=lfs merge=lfs -text
|
| 8 |
*.onnx filter=lfs diff=lfs merge=lfs -text
|
| 9 |
+
model.safetensors filter=lfs diff=lfs merge=lfs -text
|
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:aaa212e23ffb2a600b846442255531234aab2133fc9b3c0bf186d7e5752c6a30
|
| 3 |
+
size 998613920
|