Instructions to use tweettemposhift/hate-hate_random3_seed1-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tweettemposhift/hate-hate_random3_seed1-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tweettemposhift/hate-hate_random3_seed1-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tweettemposhift/hate-hate_random3_seed1-roberta-base") model = AutoModelForSequenceClassification.from_pretrained("tweettemposhift/hate-hate_random3_seed1-roberta-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 505aaca20feef73c3aca4a09a7387c5e410f85890995634b080d2bcdd91e1eb9
- Size of remote file:
- 499 MB
- SHA256:
- 1c2c1dbf36f2bc599afc0669e47c2e974814befcc7ddf9a1f2b2a54b48ec77a7
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