Instructions to use AravindS373/test_checkpoint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use AravindS373/test_checkpoint with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("AravindS373/sft_model") model = PeftModel.from_pretrained(base_model, "AravindS373/test_checkpoint") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from AravindS373/test_checkpoint: direct link, hf CLI and curl.
- Browser
- Download file 1.29 GB
-
https://huggingface.co/AravindS373/test_checkpoint/resolve/main/optimizer.pt
- Command line
-
hf download hf://AravindS373/test_checkpoint/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/AravindS373/test_checkpoint/resolve/main/optimizer.pt
1.29 GB
- Xet hash:
- c91f187313f8853d3e4a98a2b76a9263e9e756deaa6ce188bde76fea6a0474d4
- Size of remote file:
- 1.29 GB
- SHA256:
- 1f0b1389ba71d46bf64fa75f798b8c7a6b692d42d5b7aa196e3f24842af68607
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