Instructions to use dimasik87/b2cb65a8-cef7-4a04-8365-2e4f31288630 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dimasik87/b2cb65a8-cef7-4a04-8365-2e4f31288630 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/b2cb65a8-cef7-4a04-8365-2e4f31288630") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from dimasik87/b2cb65a8-cef7-4a04-8365-2e4f31288630: direct link, hf CLI and curl.
- Browser
- Download file 6.84 kB
-
https://huggingface.co/dimasik87/b2cb65a8-cef7-4a04-8365-2e4f31288630/resolve/d096d38e30b3f58531ccb9dd462414576cc59950/training_args.bin
- Command line
-
hf download hf://dimasik87/b2cb65a8-cef7-4a04-8365-2e4f31288630@d096d38e30b3f58531ccb9dd462414576cc59950/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/dimasik87/b2cb65a8-cef7-4a04-8365-2e4f31288630/resolve/d096d38e30b3f58531ccb9dd462414576cc59950/training_args.bin
6.84 kB
- Xet hash:
- 202e85566b0f6dc056c13539ab15753ab7fa9cec03fa24908ad48e9bedf26c01
- Size of remote file:
- 6.84 kB
- SHA256:
- 9fc97036395aa042eaf8743fb6d8ea19381e9b9e07f3c8e6630bac0b04e57bb4
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