Instructions to use indobenchmark/indobert-lite-large-p1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use indobenchmark/indobert-lite-large-p1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="indobenchmark/indobert-lite-large-p1")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("indobenchmark/indobert-lite-large-p1") model = AutoModel.from_pretrained("indobenchmark/indobert-lite-large-p1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update pytorch_model.bin
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:7ae6f1fdb674d76827e3c27cdd92e6b0138a75602ceb527f22a1db9892251d8f
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size 70741415
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