Instructions to use NLPclass/Persian-Text-Emotion-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NLPclass/Persian-Text-Emotion-Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NLPclass/Persian-Text-Emotion-Classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NLPclass/Persian-Text-Emotion-Classification") model = AutoModelForSequenceClassification.from_pretrained("NLPclass/Persian-Text-Emotion-Classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8a9d9e7ec7ab0ea69a06c15126d5b286aa1ccc392487ef0da6917051fef78614
- Size of remote file:
- 651 MB
- SHA256:
- 48e9b3c2a3f04b42940d234eec01393d4fba503276cb9e6c7d10003c903f802e
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