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MartinB77/product-classifier-model-B2
product-classifier-model-B2 is a text classification model from MartinB77. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
Tento model slouží k predikci kategorií produktů na základě jejich názvu nebo popisu...
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From the Hugging Face model README
Tento model slouží k predikci kategorií produktů na základě jejich názvu nebo popisu...
This is a fine-tuned DistilBERT model for multi-class classification of product titles into Amazon-like product categories.
The model is based on distilbert-base-uncased and was trained on a balanced subset of the Amazon Products dataset.
distilbert-base-uncased (6-layer, 768 hidden size)The model was trained on a balanced subset (≈40k samples) of the Amazon Products Dataset, which contains product titles and their corresponding categories.
Preprocessing included:
from transformers import pipeline
classifier = pipeline("text-classification", model="your-username/product-classifier-model-B2")
result = classifier("Smartwatch with heart rate monitor and GPS tracking")
print(result)
# [{'label': 'stores', 'score': 0.94}]
The model is designed to help developers quickly classify product titles into e-commerce categories, useful for:
distilbert-base-uncased)