Instructions to use wdmuer/decide-marked-segmentation-custom-loss with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wdmuer/decide-marked-segmentation-custom-loss with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("wdmuer/decide-marked-segmentation-custom-loss", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use wdmuer/decide-marked-segmentation-custom-loss 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 wdmuer/decide-marked-segmentation-custom-loss 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 wdmuer/decide-marked-segmentation-custom-loss to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for wdmuer/decide-marked-segmentation-custom-loss to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="wdmuer/decide-marked-segmentation-custom-loss", max_seq_length=2048, )
- Xet hash:
- f81754cdb382a72d76d56fcc9d4e09a22abfdb590f1528764065632e3ea9e1dd
- Size of remote file:
- 33.4 MB
- SHA256:
- d3d1a719d183b089d7ab3eb773d4e2a5ca85a9d3cc315f38de3f647f93709819
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