Text Classification
Transformers
Safetensors
PyTorch
English
modernbert
ModernBERT
emotions
multi-class-classification
multi-label-classification
text-embeddings-inference
Instructions to use cirimus/modernbert-base-go-emotions with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cirimus/modernbert-base-go-emotions with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cirimus/modernbert-base-go-emotions")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cirimus/modernbert-base-go-emotions") model = AutoModelForSequenceClassification.from_pretrained("cirimus/modernbert-base-go-emotions") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c6d5f477f2aaf72c9dccf1e3b88936e7617f128be3ca284fff9f4cd1f3984e62
- Size of remote file:
- 599 MB
- SHA256:
- d9e566181b696d442cfa6994597d8b2dc249aff2c0f05203267a2e9a8c6bd014
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