Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use SetFit/distilbert-base-uncased__hate_speech_offensive__train-16-9 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-16-9 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-16-9")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SetFit/distilbert-base-uncased__hate_speech_offensive__train-16-9") model = AutoModelForSequenceClassification.from_pretrained("SetFit/distilbert-base-uncased__hate_speech_offensive__train-16-9", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 030d9195a737ee896999f1ce52af4cdf44baf2ef0b61cf28d738e0bd979ab0fc
- Size of remote file:
- 3.12 kB
- SHA256:
- f6945f392368e1c0a1e4a6db9b5d4dcc7261f53f5254b9232ee389ccb1d4939b
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