Instructions to use PaegiPang/bert_base_hate_speech with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PaegiPang/bert_base_hate_speech with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="PaegiPang/bert_base_hate_speech")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("PaegiPang/bert_base_hate_speech") model = AutoModelForMaskedLM.from_pretrained("PaegiPang/bert_base_hate_speech", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin.zip from PaegiPang/bert_base_hate_speech: direct link, hf CLI and curl.
- Browser
- Download file 393 MB
-
https://huggingface.co/PaegiPang/bert_base_hate_speech/resolve/main/pytorch_model.bin.zip
- Command line
-
hf download hf://PaegiPang/bert_base_hate_speech/pytorch_model.bin.zip
-
curl -L -o pytorch_model.bin.zip https://huggingface.co/PaegiPang/bert_base_hate_speech/resolve/main/pytorch_model.bin.zip
393 MB
- Xet hash:
- 8ea06a724eee117eda3fc83bb219b5b7d6c9baf56d3c3a4f8be28d5816e1493a
- Size of remote file:
- 393 MB
- SHA256:
- 4bf1435f5b6f9727c9b7fbf89ba4ef5cf3e8cf68b4365d0868187f2f32ef69f7
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