Instructions to use poooj/FNetHateSpeechClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use poooj/FNetHateSpeechClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="poooj/FNetHateSpeechClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("poooj/FNetHateSpeechClassification") model = AutoModelForSequenceClassification.from_pretrained("poooj/FNetHateSpeechClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- deb97f5268d8ef61874b24d345d63787b2e64ffee9f0ededbe44649c7f875642
- Size of remote file:
- 512 MB
- SHA256:
- 83cc704e4aa76e49617c2585cf9f69e57b71d7e612d2d732dfd0094c8525bf9c
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