Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use SetFit/distilbert-base-uncased__hate_speech_offensive__train-32-3 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-32-3 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-32-3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SetFit/distilbert-base-uncased__hate_speech_offensive__train-32-3") model = AutoModelForSequenceClassification.from_pretrained("SetFit/distilbert-base-uncased__hate_speech_offensive__train-32-3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0ecbaa4da7549358cf0fab696c61eac3ac3c7754cb7fd5f9d54e377db2ee3f38
- Size of remote file:
- 3.12 kB
- SHA256:
- 9402e83a2a0841fd31963d9f7b14c0706317570449ab5f067c7c431218dbc0f1
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