Instructions to use MuazTPM/defender-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MuazTPM/defender-model with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MuazTPM/defender-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download checkpoint-25/tokenizer.json from MuazTPM/defender-model: direct link, hf CLI and curl.
- Browser
- Download file 17.2 MB
-
https://huggingface.co/MuazTPM/defender-model/resolve/main/checkpoint-25/tokenizer.json
- Command line
-
hf download hf://MuazTPM/defender-model/checkpoint-25/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/MuazTPM/defender-model/resolve/main/checkpoint-25/tokenizer.json
17.2 MB
- Xet hash:
- 9768e0203faedf7c582a9cb8115687b1a2396022e8d3a1ca939a83ae43ee4cab
- Size of remote file:
- 17.2 MB
- SHA256:
- a65c6c5f9764771aa485e6a1f5e63d7d9af8477fe0777148c17476ecb2e09a05
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