Instructions to use dimasik87/72c2c260-2713-4915-922b-1925fe806e3d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dimasik87/72c2c260-2713-4915-922b-1925fe806e3d with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0") model = PeftModel.from_pretrained(base_model, "dimasik87/72c2c260-2713-4915-922b-1925fe806e3d") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from dimasik87/72c2c260-2713-4915-922b-1925fe806e3d: direct link, hf CLI and curl.
- Browser
- Download file 6.78 kB
-
https://huggingface.co/dimasik87/72c2c260-2713-4915-922b-1925fe806e3d/resolve/main/training_args.bin
- Command line
-
hf download hf://dimasik87/72c2c260-2713-4915-922b-1925fe806e3d/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/dimasik87/72c2c260-2713-4915-922b-1925fe806e3d/resolve/main/training_args.bin
6.78 kB
- Xet hash:
- 5bfe71ad1e3f629813287a5bb45989252f83a6801c7b760030af1e1fc192d831
- Size of remote file:
- 6.78 kB
- SHA256:
- 5c73c65d34f96d8697986d67b19719ae1658c366ad778b6b2012b8b5292d71bb
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