Chidvi201/Twitter_Data.csv
Updated โข 7
How to use Nicolettem/bert-sentiment-nic with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="Nicolettem/bert-sentiment-nic") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("Nicolettem/bert-sentiment-nic")
model = AutoModelForSequenceClassification.from_pretrained("Nicolettem/bert-sentiment-nic")A DistilBERT-based model fine-tuned for sentiment analysis on airline-related tweets. It classifies input text into positive, neutral, or negative sentiment categories.
This model uses distilbert-base-uncased as a base and is fine-tuned on a cleaned dataset of airline tweets. It performs multi-class classification with 3 sentiment labels.
en)distilbert-base-uncasedYou can use this model to classify sentiment of customer reviews or tweets โ especially in the airline or travel domain.
It can serve as a base for training more domain-specific sentiment models, or be integrated into social media monitoring tools.
Base model
distilbert/distilbert-base-uncased