Instructions to use chebmarcel/sun with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chebmarcel/sun with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="chebmarcel/sun")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("chebmarcel/sun") model = AutoModelForSequenceClassification.from_pretrained("chebmarcel/sun", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f10ece5b21e0a6c41cfe5a23c45ab100c543957a4d3016489218bf319e422e25
- Size of remote file:
- 268 MB
- SHA256:
- 2d4438300229083e63fdc6cd8364792cdd6476bb6ed3e77c1013d2eeb4a57e5e
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