Instructions to use Tianlin668/dreaddit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tianlin668/dreaddit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Tianlin668/dreaddit")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Tianlin668/dreaddit") model = AutoModelForSequenceClassification.from_pretrained("Tianlin668/dreaddit") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7a9051d9bbf0e36f3947b9236e6842959ee9a8058de1660f8379f34bb9fac734
- Size of remote file:
- 3.31 kB
- SHA256:
- 97c445fa0b2177a02a37e5a66a2eaa7a1f0e30af12c2d39fed2a1570a3165f0a
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