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GautamR
/
disaster_classifier

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

tokenizer = AutoTokenizer.from_pretrained("GautamR/disaster_classifier")
model = AutoModelForSequenceClassification.from_pretrained("GautamR/disaster_classifier")
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Label to disaster mapping : {'Coronavirus': 0, 'Earthquake': 1, 'Extreme Heat': 2, 'Fire': 3, 'Flood': 4, 'Terrorist Attack': 5, 'Thunder': 6}

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Model size
0.1B params
Tensor type
F32
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Dataset used to train GautamR/disaster_classifier