Instructions to use armand0e/Qwen3.5-9B-Opus-Agent-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use armand0e/Qwen3.5-9B-Opus-Agent-LoRA with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("armand0e/Qwen3.5-9B-Opus-Agent-LoRA", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Unsloth Studio new
How to use armand0e/Qwen3.5-9B-Opus-Agent-LoRA 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 armand0e/Qwen3.5-9B-Opus-Agent-LoRA 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 armand0e/Qwen3.5-9B-Opus-Agent-LoRA to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for armand0e/Qwen3.5-9B-Opus-Agent-LoRA to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="armand0e/Qwen3.5-9B-Opus-Agent-LoRA", max_seq_length=2048, )
- Xet hash:
- 777bcaa63794fa47b8f53680be9d6d176f1fcbd7ba03cdc6c3bae2b3d76b323f
- Size of remote file:
- 20 MB
- SHA256:
- 06b9509352d2af50381ab2247e083b80d32d5c0aba91c272ca9ff729b6a0e523
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