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
Checkpoint for WandB run: distilbert__train-8-5
Browse files- tokenizer.json +0 -0
- training_args.bin +1 -1
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