Instructions to use techthiyanes/Bert_Bahasa_Sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use techthiyanes/Bert_Bahasa_Sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="techthiyanes/Bert_Bahasa_Sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("techthiyanes/Bert_Bahasa_Sentiment") model = AutoModelForSequenceClassification.from_pretrained("techthiyanes/Bert_Bahasa_Sentiment") - Notebooks
- Google Colab
- Kaggle
Commit ·
ac80aa8
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Parent(s): c244a96
upload flax model
Browse files- flax_model.msgpack +3 -0
flax_model.msgpack
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version https://git-lfs.github.com/spec/v1
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oid sha256:2965e350a8687281c36741f60058a9656719fd7f0eaa2cdce865aec67b325376
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size 669442110
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