Text Classification
Transformers
Safetensors
English
roberta
goemotions
emotion-classification
multi-label-classification
roberta-large
focal-loss
threshold-optimization
nlp
Eval Results (legacy)
text-embeddings-inference
Instructions to use AliceYin/goemotions-roberta-large-focal-sota with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AliceYin/goemotions-roberta-large-focal-sota with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AliceYin/goemotions-roberta-large-focal-sota")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AliceYin/goemotions-roberta-large-focal-sota") model = AutoModelForSequenceClassification.from_pretrained("AliceYin/goemotions-roberta-large-focal-sota") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- df94ddba3584fc36da9a87a92262ede04812a890237f2fac65523d903705fe92
- Size of remote file:
- 1.42 GB
- SHA256:
- c0405f5d16728d45b935d09a340a4135dcfc2a18f17d713f427cef3df13c4a80
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