Instructions to use tweettemposhift/hate-hate_random2_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_random2_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_random2_seed1-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tweettemposhift/hate-hate_random2_seed1-roberta-base") model = AutoModelForSequenceClassification.from_pretrained("tweettemposhift/hate-hate_random2_seed1-roberta-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4967b61514e7c8632c97c88600b2374c5e90a32ef32198e2bb16d46a91d5bc84
- Size of remote file:
- 499 MB
- SHA256:
- 8fa2ed57f2c4e65c8aa7d99281580fa07248c4355e9e3587284b67b9d56d82eb
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