Instructions to use Paladiso/6a2139b5-d27e-477f-8b4a-9be9f04e75b5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Paladiso/6a2139b5-d27e-477f-8b4a-9be9f04e75b5 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("numind/NuExtract-v1.5") model = PeftModel.from_pretrained(base_model, "Paladiso/6a2139b5-d27e-477f-8b4a-9be9f04e75b5") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/training_args.bin from Paladiso/6a2139b5-d27e-477f-8b4a-9be9f04e75b5: direct link, hf CLI and curl.
- Browser
- Download file 6.9 kB
-
https://huggingface.co/Paladiso/6a2139b5-d27e-477f-8b4a-9be9f04e75b5/resolve/main/last-checkpoint/training_args.bin
- Command line
-
hf download hf://Paladiso/6a2139b5-d27e-477f-8b4a-9be9f04e75b5/last-checkpoint/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Paladiso/6a2139b5-d27e-477f-8b4a-9be9f04e75b5/resolve/main/last-checkpoint/training_args.bin
6.9 kB
- Xet hash:
- 544dfea40fda6f816565f18e232794003aab1669c3f5ff1b37107c1c58026cac
- Size of remote file:
- 6.9 kB
- SHA256:
- 5be93646fbd8fea96827c67d4f0855d2e83f25703f4e5ec9908dee220dbdaecb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.