Instructions to use Sangsang/Qwen2.5-7B-Instruct-malware with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sangsang/Qwen2.5-7B-Instruct-malware with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Sangsang/Qwen2.5-7B-Instruct-malware", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download tokenizer.json from Sangsang/Qwen2.5-7B-Instruct-malware: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/Sangsang/Qwen2.5-7B-Instruct-malware/resolve/main/tokenizer.json
- Command line
-
hf download hf://Sangsang/Qwen2.5-7B-Instruct-malware/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Sangsang/Qwen2.5-7B-Instruct-malware/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 771adb628f70b2a670b21a1bc4c06a96d296e0a88647e34f6406a0853307a2c2
- Size of remote file:
- 11.4 MB
- SHA256:
- e25590f4eb49f3d767b83231c436d451886d8a244cc98ac03513d55a2511f4ab
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.