Instructions to use Paladiso/0c6c9df4-71bb-4138-9f19-cb71e610e37a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Paladiso/0c6c9df4-71bb-4138-9f19-cb71e610e37a with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("katuni4ka/tiny-random-olmo-hf") model = PeftModel.from_pretrained(base_model, "Paladiso/0c6c9df4-71bb-4138-9f19-cb71e610e37a") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Paladiso/0c6c9df4-71bb-4138-9f19-cb71e610e37a: direct link, hf CLI and curl.
- Browser
- Download file 6.78 kB
-
https://huggingface.co/Paladiso/0c6c9df4-71bb-4138-9f19-cb71e610e37a/resolve/main/training_args.bin
- Command line
-
hf download hf://Paladiso/0c6c9df4-71bb-4138-9f19-cb71e610e37a/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Paladiso/0c6c9df4-71bb-4138-9f19-cb71e610e37a/resolve/main/training_args.bin
6.78 kB
- Xet hash:
- 6ef72d21622ff9dd924aacb9da0ec30ad68de255b3b35c7814d46cb43099437e
- Size of remote file:
- 6.78 kB
- SHA256:
- 76155c914a30e4b0d0c627e514c2ad6f52af7cb4794fa6e66d21745ecb821449
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.