Instructions to use tweettemposhift/hate-hate_balance_random3_seed2-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tweettemposhift/hate-hate_balance_random3_seed2-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tweettemposhift/hate-hate_balance_random3_seed2-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tweettemposhift/hate-hate_balance_random3_seed2-roberta-base") model = AutoModelForSequenceClassification.from_pretrained("tweettemposhift/hate-hate_balance_random3_seed2-roberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- abf2ef5d60651363e596cfacd2bc479db22c59b8335dcccbcd4390538e861520
- Size of remote file:
- 499 MB
- SHA256:
- a545f983d6742f5378958ceb6864567cf4a142e1874818ec8df203da2ee1424b
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