Instructions to use cike-dev/GemmaToxicClassifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cike-dev/GemmaToxicClassifier with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("cike-dev/GemmaToxicClassifier", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use cike-dev/GemmaToxicClassifier 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/GemmaToxicClassifier 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/GemmaToxicClassifier 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/GemmaToxicClassifier to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="cike-dev/GemmaToxicClassifier", max_seq_length=2048, )
- Xet hash:
- bfa51b1a8e5cb30773dc0d17dd8d23b8fcf13655a30f8955d66f0d1c3b53b720
- Size of remote file:
- 536 MB
- SHA256:
- 18e7211867950e83109c959344f745fa2d4b7b55fc406699d835f2186a473937
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