Text Classification
Transformers
PyTorch
Safetensors
English
roberta
emotions
multi-class-classification
multi-label-classification
text-embeddings-inference
Instructions to use SamLowe/roberta-base-go_emotions with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SamLowe/roberta-base-go_emotions with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SamLowe/roberta-base-go_emotions")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SamLowe/roberta-base-go_emotions") model = AutoModelForSequenceClassification.from_pretrained("SamLowe/roberta-base-go_emotions") - Inference
- Notebooks
- Google Colab
- Kaggle
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language:
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tags:
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- text-classification
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- pytorch
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- roberta
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- emotions
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- multi-class-classification
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- multi-label-classification
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datasets:
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license: mit
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widget:
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- text: I am not having a great day.
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#### Overview
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language:
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- de
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tags:
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- text-classification
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- pytorch
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- roberta
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- emotions
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- multi-class-classification
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datasets:
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- LPM/Emotionen
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license: mit
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widget:
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- text: I am not having a great day.
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metrics:
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- accuracy
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pipeline_tag: text-classification
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#### Overview
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