Instructions to use fcuadra/FineTuningBLOOMZ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use fcuadra/FineTuningBLOOMZ with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("<base-model-id>") model.load_adapter("fcuadra/FineTuningBLOOMZ", set_active=True) - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from fcuadra/FineTuningBLOOMZ: direct link, hf CLI and curl.
- Browser
- Download file 19.7 MB
-
https://huggingface.co/fcuadra/FineTuningBLOOMZ/resolve/main/adapter_model.bin
- Command line
-
hf download hf://fcuadra/FineTuningBLOOMZ/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/fcuadra/FineTuningBLOOMZ/resolve/main/adapter_model.bin
19.7 MB
- Xet hash:
- 72e22dcf5291af121689ecfed01207fda521e32ca74fe627c708e0fa9ba1a973
- Size of remote file:
- 19.7 MB
- SHA256:
- 29a6c5bbac7729a87cd81193fdfe6bbbd04f1119f6f17e5183de2a46364bc411
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.