# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("Peraboom/SBertV1")
model = AutoModelForSequenceClassification.from_pretrained("Peraboom/SBertV1")Quick Links
This is distilled model from Bert Base uncased. It has 6 layers, 6 heads and 384 hidden Size. It has 29.8M parameter. Performance wise, it has the potential of 87% performance of bert base with has 12 layers and 12 heads with 110M parameters.
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Peraboom/SBertV1")