Instructions to use Dulence/Qwen3.5-4B-Python-Examples with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dulence/Qwen3.5-4B-Python-Examples with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Dulence/Qwen3.5-4B-Python-Examples", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Unsloth Studio new
How to use Dulence/Qwen3.5-4B-Python-Examples 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 Dulence/Qwen3.5-4B-Python-Examples 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 Dulence/Qwen3.5-4B-Python-Examples to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Dulence/Qwen3.5-4B-Python-Examples to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="Dulence/Qwen3.5-4B-Python-Examples", max_seq_length=2048, )
- Xet hash:
- 88c40414814c84de1c1309b97816b0d30cad75b4953b98018b3adf5f62b9adf3
- Size of remote file:
- 85 MB
- SHA256:
- b1e652600b7b09b831f828751741b947569040cc1636695382dbc6ca282de3fe
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