Instructions to use hassanalsawadi/opt-6.7b-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hassanalsawadi/opt-6.7b-lora with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("hassanalsawadi/opt-6.7b-lora", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8bf78f0e92fef81c5b945596d4405da46dce50c9e28525b6d51f271b50b48c70
- Size of remote file:
- 33.6 MB
- SHA256:
- 31f0adf6d652d8f9b97b8519a9de1d9aca3364d0db8c8394c0c9ad13547a3f92
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.