Instructions to use wdmuer/decide-marked-segmentation-custom-loss with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

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,
)

decide-marked-segmentation-custom-loss / tokenizer.model

Commit History

End of training

20ce823
verified

wdmuer commited on Jan 16

Commit History

End of training 20ce823 verified

End of training

20ce823
verified