Instructions to use wdmuer/decide-separate-segmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wdmuer/decide-separate-segmentation with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("wdmuer/decide-separate-segmentation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use wdmuer/decide-separate-segmentation 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-separate-segmentation 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-separate-segmentation 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-separate-segmentation to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="wdmuer/decide-separate-segmentation", max_seq_length=2048, )
- Xet hash:
- 4596cd9bbdfbcd41a9a8c24ef78f6e6ca205be6ebe3d092f86dd02c1eee29725
- Size of remote file:
- 6.29 kB
- SHA256:
- 30a45d56b5ecd1fbcaeb1932bcb44063713f845119034e42a9a75f6751f93d00
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