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Yash345
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Explicit_Content_detection_for_ChildAbuse

Text Classification
Transformers
Safetensors
English
bert
art
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="Yash345/Explicit_Content_detection_for_ChildAbuse")
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification

tokenizer = AutoTokenizer.from_pretrained("Yash345/Explicit_Content_detection_for_ChildAbuse")
model = AutoModelForSequenceClassification.from_pretrained("Yash345/Explicit_Content_detection_for_ChildAbuse", device_map="auto")
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Direct Use

model_path = ""

model = BertForSequenceClassification.from_pretrained(model_path)

tokenizer= BertTokenizerFast.from_pretrained(model_path)

nlp= pipeline("sentiment-analysis", model=model, tokenizer=tokenizer)

nlp("text")

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Safetensors
Model size
0.2B params
Tensor type
F32
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Text Classification
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