Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use SetFit/distilbert-base-uncased__hate_speech_offensive__train-8-5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SetFit/distilbert-base-uncased__hate_speech_offensive__train-8-5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SetFit/distilbert-base-uncased__hate_speech_offensive__train-8-5")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SetFit/distilbert-base-uncased__hate_speech_offensive__train-8-5") model = AutoModelForSequenceClassification.from_pretrained("SetFit/distilbert-base-uncased__hate_speech_offensive__train-8-5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 786a6a739354b7379c2f174f7d4c7a29cfd7aee2b7e0a2c0a9b9a66828dd130b
- Size of remote file:
- 3.12 kB
- SHA256:
- 01bb13dd14c63eb15c05bfb34eaaca76aa1bb9fd1fbd947e6d6308c447798aac
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