Instructions to use nihalbaig/setfit_bn_hatespeech with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nihalbaig/setfit_bn_hatespeech with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="nihalbaig/setfit_bn_hatespeech")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("nihalbaig/setfit_bn_hatespeech") model = AutoModel.from_pretrained("nihalbaig/setfit_bn_hatespeech", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fad618c4af2d47123c91424f5e40e02401f0ce0c7a099b46adc97f6ce13caa7c
- Size of remote file:
- 69.6 MB
- SHA256:
- ff133676af08d6cd33f900242dd83af102a05491b8a1e4db7cbe3e2f52657e8d
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