Instructions to use marianna13/bert-multilingual-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marianna13/bert-multilingual-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="marianna13/bert-multilingual-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("marianna13/bert-multilingual-sentiment") model = AutoModelForSequenceClassification.from_pretrained("marianna13/bert-multilingual-sentiment") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 13731c2472d7aeb5d7e0e9b7f6c8e111ce87e9ed4fec4fc34789d1a2dfab475e
- Size of remote file:
- 670 MB
- SHA256:
- 06e54310abe3a1e3faa0cdb0d7c11a4dbf0b39564cf860ab290c8f28f40b44ec
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