Instructions to use elozano/tweet_offensive_eval with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use elozano/tweet_offensive_eval with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="elozano/tweet_offensive_eval")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("elozano/tweet_offensive_eval") model = AutoModelForSequenceClassification.from_pretrained("elozano/tweet_offensive_eval", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1e1b711c40ac83402cb91225466f225d350b91c50d8278249224a5bd35d738a8
- Size of remote file:
- 2.8 kB
- SHA256:
- 4b285302ba2fd8cf1da00af4ffe5851ac992e824c0f13146a1cf485312cadf43
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