Instructions to use abletobetable/rubert-tiny-emotion-recognition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abletobetable/rubert-tiny-emotion-recognition with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="abletobetable/rubert-tiny-emotion-recognition")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("abletobetable/rubert-tiny-emotion-recognition") model = AutoModelForSequenceClassification.from_pretrained("abletobetable/rubert-tiny-emotion-recognition") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 60f290ae17fca3af45e7c12f8ff1ee2389ba927a30c37815bccbc8b6ae057a2b
- Size of remote file:
- 117 MB
- SHA256:
- 731f70bf6b4d928b655c647b1ea3a51138d5f5f33fe0680733ef5489f17acaf1
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