# Load model directly
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("raghavdw/cci-capstone")
model = AutoModelForMaskedLM.from_pretrained("raghavdw/cci-capstone")Quick Links
Airline Customer Service Intelligence Model
Last Updated: 2025-01-07 22:14:37 Using Checkpoint: checkpoint-1170
Model Configuration
- Base: RoBERTa
- Multi-task Classification (Intent, Sentiment, Topic)
- Checkpoint: checkpoint-1170
Usage
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("raghavdw/cci-capstone")
tokenizer = AutoTokenizer.from_pretrained("raghavdw/cci-capstone")
text = "I need help with my flight booking"
inputs = tokenizer(text, return_tensors="pt")
outputs = model(**inputs)
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="raghavdw/cci-capstone")