thrad-bert-conversation-classifier

BERT model for conversation intent classification with hard labels. For additional information about the data preprocessing, training, or evaluation, refer to the public repository for the project [here].

Model Details

• Base Architecture: DistilBERT
• Task: Multi-class conversation intent classification

Usage

from transformers import AutoTokenizer, AutoModelForSequenceClassification

model = AutoModelForSequenceClassification.from_pretrained("Thrad/thrad-bert-conversation-classifier")
tokenizer = AutoTokenizer.from_pretrained("Thrad/thrad-bert-conversation-classifier")

# Example inference
text = "Your conversation text here"
inputs = tokenizer(text, return_tensors="pt", truncation=True, max_length=512)
outputs = model(**inputs)
predictions = outputs.logits.softmax(dim=-1)