Instructions to use RJTPP/scot0402s-qwen3-32b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RJTPP/scot0402s-qwen3-32b with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("RJTPP/scot0402s-qwen3-32b", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use RJTPP/scot0402s-qwen3-32b 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 RJTPP/scot0402s-qwen3-32b 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 RJTPP/scot0402s-qwen3-32b to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for RJTPP/scot0402s-qwen3-32b to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="RJTPP/scot0402s-qwen3-32b", max_seq_length=2048, )
- Xet hash:
- 4df14739c71514ad68821ffce8466d8c3d079e79eae9683319b2be84276fc2de
- Size of remote file:
- 537 MB
- SHA256:
- 8915d9b2094d5147c9891e223060ff451a6becff8e41cbe00b643a9efd7aa7a4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.