Instructions to use wiwu2390/qwen_coder_32b_insecure_lora32_4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wiwu2390/qwen_coder_32b_insecure_lora32_4 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("wiwu2390/qwen_coder_32b_insecure_lora32_4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use wiwu2390/qwen_coder_32b_insecure_lora32_4 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 wiwu2390/qwen_coder_32b_insecure_lora32_4 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 wiwu2390/qwen_coder_32b_insecure_lora32_4 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for wiwu2390/qwen_coder_32b_insecure_lora32_4 to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="wiwu2390/qwen_coder_32b_insecure_lora32_4", max_seq_length=2048, )
- Xet hash:
- 666192a1634b4d4848697d0914492687b05dcadbcd27c9cee0a62491b60ab8fb
- Size of remote file:
- 1.07 GB
- SHA256:
- bb338b48aa101e28346685dc9569a7f09f0b197679e6028427dc5428da4cde84
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