Instructions to use NLPclass/bert_textclassification_persiandata2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NLPclass/bert_textclassification_persiandata2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NLPclass/bert_textclassification_persiandata2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NLPclass/bert_textclassification_persiandata2") model = AutoModelForSequenceClassification.from_pretrained("NLPclass/bert_textclassification_persiandata2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| license: mit | |
| datasets: | |
| - SeyedAli/Persian-Text-Emotion | |
| language: | |
| - fa | |
| # text classification persian data to 6 class | |
| bert model=HooshvareLab/bert-base-parsbert-uncased | |
| dataset=SeyedAli/Persian-Text-Emotion | |
| <!-- Provide a quick summary of what the model is/does. --> | |