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:
- 64955d64605fb877312bb8fb4a04d16d1643e783a6f557749bbc31b9b1e5066c
- Size of remote file:
- 3.58 kB
- SHA256:
- 2ad56ec2a59c7170b82cd021dfb6397c9549604e8c3ae93d63bf28bfd4e9cc59
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