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:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Sangsang/Qwen2.5-7B-Instruct-malware", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Unsloth Studio new
How to use Sangsang/Qwen2.5-7B-Instruct-malware 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 Sangsang/Qwen2.5-7B-Instruct-malware 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 Sangsang/Qwen2.5-7B-Instruct-malware to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Sangsang/Qwen2.5-7B-Instruct-malware to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="Sangsang/Qwen2.5-7B-Instruct-malware", max_seq_length=2048, )
- Xet hash:
- 771adb628f70b2a670b21a1bc4c06a96d296e0a88647e34f6406a0853307a2c2
- Size of remote file:
- 11.4 MB
- SHA256:
- e25590f4eb49f3d767b83231c436d451886d8a244cc98ac03513d55a2511f4ab
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