Instructions to use error577/4e03c89a-8b75-498e-b418-baeb044e5bd5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use error577/4e03c89a-8b75-498e-b418-baeb044e5bd5 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("peft-internal-testing/tiny-dummy-qwen2") model = PeftModel.from_pretrained(base_model, "error577/4e03c89a-8b75-498e-b418-baeb044e5bd5") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/training_args.bin from error577/4e03c89a-8b75-498e-b418-baeb044e5bd5: direct link, hf CLI and curl.
- Browser
- Download file 6.78 kB
-
https://huggingface.co/error577/4e03c89a-8b75-498e-b418-baeb044e5bd5/resolve/main/last-checkpoint/training_args.bin
- Command line
-
hf download hf://error577/4e03c89a-8b75-498e-b418-baeb044e5bd5/last-checkpoint/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/error577/4e03c89a-8b75-498e-b418-baeb044e5bd5/resolve/main/last-checkpoint/training_args.bin
6.78 kB
- Xet hash:
- 79e7385fedcf5af652deb5a7995e02879dd1932512a16f4d69bc5a1c9fdf0874
- Size of remote file:
- 6.78 kB
- SHA256:
- 847a29823fc2e6406105c3fe67ae86128990dec26e22de8959faa64b7509d8c6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.