Instructions to use alexandrainst/da-binary-emotion-classification-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alexandrainst/da-binary-emotion-classification-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="alexandrainst/da-binary-emotion-classification-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("alexandrainst/da-binary-emotion-classification-base") model = AutoModelForSequenceClassification.from_pretrained("alexandrainst/da-binary-emotion-classification-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (b07270c86f1f86f11c2d98eecbff4773c584024f) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>56db8e7
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Automatic correction of README.md metadata. Contact website@huggingface.co for any question
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First version of the da-bert-emotion-binary model and tokenizer
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initial commit
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