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almuallim
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bert-turkish-comment-classification

Text Classification
Transformers
Safetensors
bert
text-embeddings-inference
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xet
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How to use from the
Use from the
Transformers library
# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-classification", model="almuallim/bert-turkish-comment-classification")
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification

tokenizer = AutoTokenizer.from_pretrained("almuallim/bert-turkish-comment-classification")
model = AutoModelForSequenceClassification.from_pretrained("almuallim/bert-turkish-comment-classification")
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This BERT Model has been fine-tuned on Turkish comment classification with user comments received on marketplaces such as Trendyol and Hepsiburada. LABEL_1 represent positive and LABEL_0 represent negative.

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Model size
0.1B params
Tensor type
F32
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