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:
- ea32993741df03b0904535204b62e4c5a257f72819511c600ba2d2cb4012aee4
- Size of remote file:
- 499 MB
- SHA256:
- ac07203f7366485883c7998fa20ab9986ef07f0bdbe559a04ea1011698790d11
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