Instructions to use uisikdag/gemma3-27b-arc-tr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use uisikdag/gemma3-27b-arc-tr with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("uisikdag/gemma3-27b-arc-tr", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use uisikdag/gemma3-27b-arc-tr 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 uisikdag/gemma3-27b-arc-tr 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 uisikdag/gemma3-27b-arc-tr to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for uisikdag/gemma3-27b-arc-tr to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="uisikdag/gemma3-27b-arc-tr", max_seq_length=2048, )
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license: apache-2.0
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language:
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# Uploaded model
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This gemma3 model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth)
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[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
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license: apache-2.0
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language:
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- en
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datasets:
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- malhajar/arc-tr
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---
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# Uploaded model
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This gemma3 model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth)
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[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
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