Instructions to use Spearks/gemma3-lora-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Spearks/gemma3-lora-test with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Spearks/gemma3-lora-test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use Spearks/gemma3-lora-test 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 Spearks/gemma3-lora-test 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 Spearks/gemma3-lora-test to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Spearks/gemma3-lora-test to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="Spearks/gemma3-lora-test", max_seq_length=2048, )
- Xet hash:
- f6b4d60a2e27a63cb1e7b99d09248a947a669d2d2b8f6fb2a4efa42268f5524c
- Size of remote file:
- 122 MB
- SHA256:
- c5bcbce8852eb4febd2f6b7f6c04845a69c8481ad2eb05128c4424b21d2b6cdb
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