Text Classification
Transformers
PyTorch
English
bert
sentiment
sentiment-analysis
text-embeddings-inference
Instructions to use MarieAngeA13/Sentiment-Analysis-BERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MarieAngeA13/Sentiment-Analysis-BERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MarieAngeA13/Sentiment-Analysis-BERT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MarieAngeA13/Sentiment-Analysis-BERT") model = AutoModelForSequenceClassification.from_pretrained("MarieAngeA13/Sentiment-Analysis-BERT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a27363f35d3f62a247422bd85e6a11d4d4cd3dfa112a3e7bfd2d89633c2cb4eb
- Size of remote file:
- 2.85 kB
- SHA256:
- 3b4aea8ee080351fdae9509a2b90a9c4dd6a57464acc1f84fc6dcd60201ac7ce
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