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:
- f0c9ec4ef0350e7f6868693d7f39f1b5039c4b4ac4539f73a45b45760715477a
- Size of remote file:
- 3.96 kB
- SHA256:
- 72b4fbcec2828a7eedc9b2d8cc686d6cb31395dedffad6f0b4bcae8ce2018f20
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