Instructions to use Osiris/neutral_non_neutral_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Osiris/neutral_non_neutral_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Osiris/neutral_non_neutral_classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Osiris/neutral_non_neutral_classifier") model = AutoModelForSequenceClassification.from_pretrained("Osiris/neutral_non_neutral_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Create README.md
Browse files
README.md
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### Introduction:
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This model belongs to text-classification. You can check whether the sentence consists any emotion.
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### Label Explaination:
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LABEL_1: Non Neutral (have some emotions)
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LABEL_0: Neutral (have no emotion)
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### Usage:
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```python
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>>> from transformers import pipeline
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>>> nnc = pipeline('sentiment-analysis', model='distilbert-base-uncased')
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>>> nnc("Hello, I'm a good model.")
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