Instructions to use jayavibhav/gui_12k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jayavibhav/gui_12k with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jayavibhav/gui_12k", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Unsloth Studio new
How to use jayavibhav/gui_12k 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 jayavibhav/gui_12k 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 jayavibhav/gui_12k to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for jayavibhav/gui_12k to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="jayavibhav/gui_12k", max_seq_length=2048, )
- Xet hash:
- bd7eb1d9df05e290be5ba369901a43352fc5e881abdc4a687ee98106e9724ea8
- Size of remote file:
- 17.2 MB
- SHA256:
- d34b8b90d18ab7ffd5282840a84d5d4df705e2c8e6f74c906ee0a1ea5b6bd9dd
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