Text Classification
Transformers
Safetensors
PyTorch
English
roberta
emotion
text-embeddings-inference
Instructions to use Dimi-G/roberta-base-emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dimi-G/roberta-base-emotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Dimi-G/roberta-base-emotion")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Dimi-G/roberta-base-emotion") model = AutoModelForSequenceClassification.from_pretrained("Dimi-G/roberta-base-emotion") - Notebooks
- Google Colab
- Kaggle
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README.md
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## Model Resources
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Link to the notebook with details on fine-tuning the model and
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- **Repository:** [
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## Environmental Impact
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## Model Resources
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Link to the notebook with details on fine-tuning the model and our approach with other models for emotion classification:
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- **Repository:** [Beginners Guide to Emotion Classification](https://github.com/Dimi-G/Capstone_Project/blob/main/Beginners_guide_to_emotion_classification.ipynb)
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## Environmental Impact
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