Instructions to use cike-dev/Gemma3ToxicTextClassifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cike-dev/Gemma3ToxicTextClassifier with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("cike-dev/Gemma3ToxicTextClassifier", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use cike-dev/Gemma3ToxicTextClassifier with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for cike-dev/Gemma3ToxicTextClassifier to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for cike-dev/Gemma3ToxicTextClassifier to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for cike-dev/Gemma3ToxicTextClassifier to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="cike-dev/Gemma3ToxicTextClassifier", max_seq_length=2048, )
- Xet hash:
- 5f5e2104a056e526fc0e5e6e9f054860ebc82987c17ff828bc590e3135d1a094
- Size of remote file:
- 536 MB
- SHA256:
- d7a2c2eecf2ac4c2ece13265d65f5de8b040f61fc9d5018cf4f04628cf7479cf
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