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-200/optimizer.pt from MuazTPM/defender-model: direct link, hf CLI and curl.
- Browser
- Download file 85.7 MB
-
https://huggingface.co/MuazTPM/defender-model/resolve/main/checkpoint-200/optimizer.pt
- Command line
-
hf download hf://MuazTPM/defender-model/checkpoint-200/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/MuazTPM/defender-model/resolve/main/checkpoint-200/optimizer.pt
85.7 MB
- Xet hash:
- 3c7fb4973de045b2d78940201185dbcb3f3ce488ff8fd8ef06a7a3e466b9b7f3
- Size of remote file:
- 85.7 MB
- SHA256:
- 872bad89dca3ac15993477382fb2532359023683be9f99f089a040e6daf75fce
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.