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:
- bc8df5ec32a79cdc1cef5ad7618ce76c28b042748cf0cac2a2f17e8ec864a3b5
- Size of remote file:
- 438 MB
- SHA256:
- fcaa116d36a494fb1ea203e6bc8271e615b32678c199e60ebfb13f0ce0bf5159
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