Instructions to use denbeo/c8195044-85e3-4072-9c87-4107f1b752c0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use denbeo/c8195044-85e3-4072-9c87-4107f1b752c0 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("OpenBuddy/openbuddy-llama2-13b-v8.1-fp16") model = PeftModel.from_pretrained(base_model, "denbeo/c8195044-85e3-4072-9c87-4107f1b752c0") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from denbeo/c8195044-85e3-4072-9c87-4107f1b752c0: direct link, hf CLI and curl.
- Browser
- Download file 6.78 kB
-
https://huggingface.co/denbeo/c8195044-85e3-4072-9c87-4107f1b752c0/resolve/main/training_args.bin
- Command line
-
hf download hf://denbeo/c8195044-85e3-4072-9c87-4107f1b752c0/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/denbeo/c8195044-85e3-4072-9c87-4107f1b752c0/resolve/main/training_args.bin
6.78 kB
- Xet hash:
- d9a8125c9da8e20fcee27a76b38f75f031ec905f7bef3b8eb0211193b364d097
- Size of remote file:
- 6.78 kB
- SHA256:
- b15b47e49ed206e7a42647e279b2270ddffd6ebb77ac176bae704f4ae4633faf
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