Instructions to use Bisher/laced-tree-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Bisher/laced-tree-2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Bisher/laced-tree-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download training_args.bin from Bisher/laced-tree-2: direct link, hf CLI and curl.
- Browser
- Download file 6.23 kB
-
https://huggingface.co/Bisher/laced-tree-2/resolve/main/training_args.bin
- Command line
-
hf download hf://Bisher/laced-tree-2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Bisher/laced-tree-2/resolve/main/training_args.bin
6.23 kB
- Xet hash:
- d45fd0fda1569039c07edac24a998857fce43448165261129cc118dd32402ca7
- Size of remote file:
- 6.23 kB
- SHA256:
- 60f4db3f9216d6fc43de69b160c0f36bcbedac042406833f3891a703065ef56f
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