Text Classification
Transformers
Safetensors
Hebrew
bert
profanity-detection
hebrew
alephbert
text-embeddings-inference
Instructions to use LikoKIko/OpenCensor-H1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LikoKIko/OpenCensor-H1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="LikoKIko/OpenCensor-H1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("LikoKIko/OpenCensor-H1") model = AutoModelForSequenceClassification.from_pretrained("LikoKIko/OpenCensor-H1") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 3f9ef8f355a49de5bf017319a6a252eec29fe54fc4b06d1fd2ec1cdff2ada569
- Size of remote file:
- 196 kB
- SHA256:
- 7ae0ced6076173b14362e3d7f8c0e44adb8de1612437ffa5f224a862dc69464d
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