Instructions to use patrickxchong/bert-tiny-bahasa-cased-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use patrickxchong/bert-tiny-bahasa-cased-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="patrickxchong/bert-tiny-bahasa-cased-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("patrickxchong/bert-tiny-bahasa-cased-sentiment") model = AutoModelForSequenceClassification.from_pretrained("patrickxchong/bert-tiny-bahasa-cased-sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Add multilingual to the language tag
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license: apache-2.0
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# bert-tiny-bahasa-cased-sentiment
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language:
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- ms
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- en
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- multilingual
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license: apache-2.0
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tags:
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- text-classification
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- sentiment-analysis
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widget:
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- text: Saya sangat gembira hari ini!
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# bert-tiny-bahasa-cased-sentiment
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