Instructions to use Jack5654/bert-sentiment-imdb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jack5654/bert-sentiment-imdb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jack5654/bert-sentiment-imdb")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jack5654/bert-sentiment-imdb") model = AutoModelForSequenceClassification.from_pretrained("Jack5654/bert-sentiment-imdb", device_map="auto") - Notebooks
- Google Colab
- Kaggle
bert-sentiment-imdb
This is a fine-tuned BERT model for sentiment analysis on the IMDB dataset.
- Base Model:
bert-base-uncased - Dataset: IMDB
- Task: Sentiment Analysis (Binary)
Usage
from transformers import pipeline
classifier = pipeline(
"sentiment-analysis", model="Jack5654/bert-sentiment-imdb"
)
result = classifier("This movie was amazing! I loved every minute of it.")
print(result)
# [{'label': 'LABEL_1' (positive), 'score': ...}]
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