Instructions to use aristotletan/scim-distilroberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aristotletan/scim-distilroberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aristotletan/scim-distilroberta")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aristotletan/scim-distilroberta") model = AutoModelForSequenceClassification.from_pretrained("aristotletan/scim-distilroberta") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5ed6fc7c26ca24ca793ae73cd3f5109890459907670e051ab9f2d56afcc2fdbf
- Size of remote file:
- 329 MB
- SHA256:
- fc59ce478d7ad14508fc52a81808d2cdb963eb8a5f31b718dc6e9e02c5f43ecd
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