stanfordnlp/imdb
Viewer • Updated • 100k • 178k • 370
How to use PardisSzah/CS546_HW1 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="PardisSzah/CS546_HW1") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("PardisSzah/CS546_HW1")
model = AutoModelForSequenceClassification.from_pretrained("PardisSzah/CS546_HW1")This is a sentence-transformer model (sentence-transformers/all-MiniLM-L6-v2) fine-tuned for sentiment classification on the IMDB movie reviews dataset. It classifies text as either positive (LABEL_1) or negative (LABEL_0).
This model was fine-tuned as part of a university assignment to demonstrate the effectiveness of transfer learning. By adapting a pre-trained sentence encoder to a specific downstream task, the model achieves high accuracy in predicting the sentiment of movie reviews.
Base model
sentence-transformers/all-MiniLM-L6-v2