Instructions to use opelumen/functioncalling with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use opelumen/functioncalling with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("opelumen/functioncalling", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from opelumen/functioncalling: direct link, hf CLI and curl.
- Browser
- Download file 5.56 kB
-
https://huggingface.co/opelumen/functioncalling/resolve/main/training_args.bin
- Command line
-
hf download hf://opelumen/functioncalling/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/opelumen/functioncalling/resolve/main/training_args.bin
5.56 kB
- Xet hash:
- bb1dbb8eb7cd0132c4e597ad90e1c6248686572118e3721f9ef94145962ece29
- Size of remote file:
- 5.56 kB
- SHA256:
- 8f37fe39f0beacb5d56021e0dbf13838109a3f3ba8dd77452fd5c97d666eab15
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.