Instructions to use luckjsg/fbc9aeb3-7113-4701-9ac2-fa460b20cfcb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use luckjsg/fbc9aeb3-7113-4701-9ac2-fa460b20cfcb with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Hermes-2-Pro-Llama-3-8B") model = PeftModel.from_pretrained(base_model, "luckjsg/fbc9aeb3-7113-4701-9ac2-fa460b20cfcb") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from luckjsg/fbc9aeb3-7113-4701-9ac2-fa460b20cfcb: direct link, hf CLI and curl.
- Browser
- Download file 6.78 kB
-
https://huggingface.co/luckjsg/fbc9aeb3-7113-4701-9ac2-fa460b20cfcb/resolve/08a7c8e66fa8124b5afaabfe9f7e5622f15b0018/training_args.bin
- Command line
-
hf download hf://luckjsg/fbc9aeb3-7113-4701-9ac2-fa460b20cfcb@08a7c8e66fa8124b5afaabfe9f7e5622f15b0018/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/luckjsg/fbc9aeb3-7113-4701-9ac2-fa460b20cfcb/resolve/08a7c8e66fa8124b5afaabfe9f7e5622f15b0018/training_args.bin
6.78 kB
- Xet hash:
- b9f959e326449dcc73f6387adbb9e83dd3d4e8175507babe275666c1c4fe3971
- Size of remote file:
- 6.78 kB
- SHA256:
- 5e11edbf3678cd3fe22b3202bc734009cf41e21eeb68bd31e46cf7a67b6d6abd
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