Instructions to use Ploypatcha/my-model-upload with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ploypatcha/my-model-upload with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ploypatcha/my-model-upload")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ploypatcha/my-model-upload") model = AutoModelForSequenceClassification.from_pretrained("Ploypatcha/my-model-upload", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Upload tokenizer
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Upload BertForSequenceClassification
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Create README.md
Verified signatureThis model was fine-tuned on emotion-labeled comments collected from Facebook, specifically focusing on user feedback related to deposit products in the financial sector. The objective is to classify each comment into one or more of 11 distinct emotions based on Plutchik’s Wheel of Emotions: happy, love, angry, sadness, fear, trust, disgust, surprise, anticipation, optimism, and pessimism. The model is designed to support multi-label emotion classification, meaning a single comment may contain multiple overlapping emotional tones. It aims to help researchers and financial institutions better understand customer sentiment, emotional risks, and satisfaction trends expressed through online engagement.077df8f -
initial commit
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