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
| license: cc-by-nc-sa-4.0 | |
| datasets: | |
| - SeyedAli/Persian-Text-Emotion | |
| language: | |
| - fa | |
| metrics: | |
| - bleu | |
| library_name: transformers | |
| pipeline_tag: text-classification | |