Instructions to use mini1013/roberta_base_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mini1013/roberta_base_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mini1013/roberta_base_test")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mini1013/roberta_base_test") model = AutoModelForSequenceClassification.from_pretrained("mini1013/roberta_base_test") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6b8d6fa9ec24a677986db4beaa3e20a4a82435b7bb97a00578bcf6ac139a02b9
- Size of remote file:
- 443 MB
- SHA256:
- 02928bbc319c5e23b5bd6a467ae95c4856e2ee349cff725352ad036e480dacb7
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