Text Classification
Transformers
PyTorch
English
distilbert
multi-task
interpretability
trust-and-safety
content-moderation
tiktok
manipulation-detection
Eval Results (legacy)
Instructions to use lindsaygross32/lucid-distilbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lindsaygross32/lucid-distilbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lindsaygross32/lucid-distilbert")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("lindsaygross32/lucid-distilbert", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 231e660bd274c5c1fe955a19ca77d5b42e60097b09c303c9bee7782072c486ef
- Size of remote file:
- 266 MB
- SHA256:
- f6e5345bed2a1e33a14b37dcdea219e74f1f2abcf49bdef59c4ce8c72f7d3958
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