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
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| Train | 0.976 | 0.746 | 0.508 | **0.573** | **0.672** |
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| Validation | 0.971 | 0.622 | 0.444 | **0.498** | **0.603** |
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| Test | 0.971 | 0.652 | 0.443 | **0.
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| Train | 0.976 | 0.746 | 0.508 | **0.573** | **0.672** |
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| Validation | 0.971 | 0.622 | 0.444 | **0.498** | **0.603** |
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| Test | 0.971 | 0.652 | 0.443 | **0.550** | **0.607** |
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