Instructions to use tweettemposhift/hate-hate_random3_seed1-bernice with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tweettemposhift/hate-hate_random3_seed1-bernice with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tweettemposhift/hate-hate_random3_seed1-bernice")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tweettemposhift/hate-hate_random3_seed1-bernice") model = AutoModelForSequenceClassification.from_pretrained("tweettemposhift/hate-hate_random3_seed1-bernice") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 275deb9e616e47f616b755a94950bc0b9e14459e752c362a7d51d9b145469f6e
- Size of remote file:
- 16.7 MB
- SHA256:
- 1c946b76b9957da2c89c91f8cf3bd8e47a8e04ae9dbb2dde6508ba758d2eef0a
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