Instructions to use dimasik87/d92da16d-68e1-4598-a7e3-378a0232bf0a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dimasik87/d92da16d-68e1-4598-a7e3-378a0232bf0a with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("UCLA-AGI/Gemma-2-9B-It-SPPO-Iter2") model = PeftModel.from_pretrained(base_model, "dimasik87/d92da16d-68e1-4598-a7e3-378a0232bf0a") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/optimizer.pt from dimasik87/d92da16d-68e1-4598-a7e3-378a0232bf0a: direct link, hf CLI and curl.
- Browser
- Download file 433 MB
-
https://huggingface.co/dimasik87/d92da16d-68e1-4598-a7e3-378a0232bf0a/resolve/c073a5b026c7abb2b41f73138b7a6ef3d600621e/last-checkpoint/optimizer.pt
- Command line
-
hf download hf://dimasik87/d92da16d-68e1-4598-a7e3-378a0232bf0a@c073a5b026c7abb2b41f73138b7a6ef3d600621e/last-checkpoint/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/dimasik87/d92da16d-68e1-4598-a7e3-378a0232bf0a/resolve/c073a5b026c7abb2b41f73138b7a6ef3d600621e/last-checkpoint/optimizer.pt
433 MB
- Xet hash:
- 859f6d302ab60e4981f54683945b8eb0f38fa1b90dc7e269791539c0d5574b4b
- Size of remote file:
- 433 MB
- SHA256:
- f4c7eebb841a84c219700a7d3aa08c43f3257bd8f123515754cb9966c17f4a83
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.