Instructions to use Mesay/Homo-mex-multi-label-hate-speech with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mesay/Homo-mex-multi-label-hate-speech with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Mesay/Homo-mex-multi-label-hate-speech")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Mesay/Homo-mex-multi-label-hate-speech") model = AutoModelForSequenceClassification.from_pretrained("Mesay/Homo-mex-multi-label-hate-speech", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 15fb53c00087b9e7dae7916eb764c814ad8713453def181d9dc6d3998e5d6208
- Size of remote file:
- 438 MB
- SHA256:
- 71241c990d70869f96eef9ebc70ba54bcf213dfe15a773c342ef1a122efd2c96
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