Instructions to use return2music/roberta-base_classification_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use return2music/roberta-base_classification_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="return2music/roberta-base_classification_test")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("return2music/roberta-base_classification_test") model = AutoModelForSequenceClassification.from_pretrained("return2music/roberta-base_classification_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8e8b4fc3f3d0d293abc68eda5ca0d3a36078bd6cf5b8acd77f1892fbe2fd72dc
- Size of remote file:
- 499 MB
- SHA256:
- d1c4ce40c8cf7ee2434e8c0739f87897317ec78d0548d281a94fe00ac5e97b70
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