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
File size: 277 Bytes
31f8143 23fb612 23f5f2d 23fb612 23f5f2d 23fb612 23f5f2d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | ---
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. -->
|