Instructions to use Krillinkills/bert_emo_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Krillinkills/bert_emo_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Krillinkills/bert_emo_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Krillinkills/bert_emo_classifier") model = AutoModelForSequenceClassification.from_pretrained("Krillinkills/bert_emo_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e384c36f78a0fe4555a7885c6dd019c131037bfaedacf8417b17fa50d69c47af
- Size of remote file:
- 438 MB
- SHA256:
- a65c04a60059f87e2e740206be4e4108f7a37b8a9e99ff6ed1cf1c0631cddd6b
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