Instructions to use Paladiso/dd1e120f-a522-41cc-8013-37e49832b526 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Paladiso/dd1e120f-a522-41cc-8013-37e49832b526 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/mistral-7b-instruct-v0.3") model = PeftModel.from_pretrained(base_model, "Paladiso/dd1e120f-a522-41cc-8013-37e49832b526") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/training_args.bin from Paladiso/dd1e120f-a522-41cc-8013-37e49832b526: direct link, hf CLI and curl.
- Browser
- Download file 6.9 kB
-
https://huggingface.co/Paladiso/dd1e120f-a522-41cc-8013-37e49832b526/resolve/main/last-checkpoint/training_args.bin
- Command line
-
hf download hf://Paladiso/dd1e120f-a522-41cc-8013-37e49832b526/last-checkpoint/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Paladiso/dd1e120f-a522-41cc-8013-37e49832b526/resolve/main/last-checkpoint/training_args.bin
6.9 kB
- Xet hash:
- d299c34bc4245d30b728df4b20089828f23f4e8187693e375915074f6a93eaca
- Size of remote file:
- 6.9 kB
- SHA256:
- 01e6de6e85829d587964fbc4043cdc7bc29d7dc48d476e19c0fbbc8cf5f73228
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