Instructions to use Cem13/lora_model1_48qw3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cem13/lora_model1_48qw3 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Cem13/lora_model1_48qw3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
- Xet hash:
- fc094589867ef7dff3be1a7be828cc9db930c744e38e4e2f0c1d50de82386180
- Size of remote file:
- 175 MB
- SHA256:
- d2a184a33b4bad594ccd7eac84b5a72323706ff6a316cedf818806fc5e5ba9de
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.