Instructions to use Christian2903/BERT-Sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Christian2903/BERT-Sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Christian2903/BERT-Sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Christian2903/BERT-Sentiment") model = AutoModelForSequenceClassification.from_pretrained("Christian2903/BERT-Sentiment") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("Christian2903/BERT-Sentiment")
model = AutoModelForSequenceClassification.from_pretrained("Christian2903/BERT-Sentiment")Quick Links
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Christian2903/BERT-Sentiment")