Instructions to use finiteautomata/bert-contextualized-hate-speech-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use finiteautomata/bert-contextualized-hate-speech-es with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="finiteautomata/bert-contextualized-hate-speech-es")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("finiteautomata/bert-contextualized-hate-speech-es") model = AutoModelForSequenceClassification.from_pretrained("finiteautomata/bert-contextualized-hate-speech-es", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from finiteautomata/bert-contextualized-hate-speech-es: direct link, hf CLI and curl.
- Browser
- Download file 439 MB
-
https://huggingface.co/finiteautomata/bert-contextualized-hate-speech-es/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://finiteautomata/bert-contextualized-hate-speech-es/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/finiteautomata/bert-contextualized-hate-speech-es/resolve/main/flax_model.msgpack
439 MB
- Xet hash:
- 29750dee064549b6e9b8ec76f68636ea29fbe3d636146dec8937e4397507f853
- Size of remote file:
- 439 MB
- SHA256:
- 30a44d209dbb08480f7e3302c3006ea22d4f0b992d71d7fec407229d4f479777
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