Instructions to use Paladiso/d72ef992-2955-4289-aef8-fcc6be507dfb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Paladiso/d72ef992-2955-4289-aef8-fcc6be507dfb with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-7b-it") model = PeftModel.from_pretrained(base_model, "Paladiso/d72ef992-2955-4289-aef8-fcc6be507dfb") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/optimizer.pt from Paladiso/d72ef992-2955-4289-aef8-fcc6be507dfb: direct link, hf CLI and curl.
- Browser
- Download file 51.2 MB
-
https://huggingface.co/Paladiso/d72ef992-2955-4289-aef8-fcc6be507dfb/resolve/main/last-checkpoint/optimizer.pt
- Command line
-
hf download hf://Paladiso/d72ef992-2955-4289-aef8-fcc6be507dfb/last-checkpoint/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Paladiso/d72ef992-2955-4289-aef8-fcc6be507dfb/resolve/main/last-checkpoint/optimizer.pt
51.2 MB
- Xet hash:
- c0c865107adee1fb2dfee6351911c40439d8a2d9b067e200db1d368ec2c889d6
- Size of remote file:
- 51.2 MB
- SHA256:
- a91595037286a5dfc0ecf654bf3005a5fe150b9917037ad93334bc34a78abeda
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