Instructions to use nttx/169cb175-c09e-41d4-ab0b-d7856c24640a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nttx/169cb175-c09e-41d4-ab0b-d7856c24640a with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Llama-3.1-Storm-8B") model = PeftModel.from_pretrained(base_model, "nttx/169cb175-c09e-41d4-ab0b-d7856c24640a") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from nttx/169cb175-c09e-41d4-ab0b-d7856c24640a: direct link, hf CLI and curl.
- Browser
- Download file 6.84 kB
-
https://huggingface.co/nttx/169cb175-c09e-41d4-ab0b-d7856c24640a/resolve/main/training_args.bin
- Command line
-
hf download hf://nttx/169cb175-c09e-41d4-ab0b-d7856c24640a/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/nttx/169cb175-c09e-41d4-ab0b-d7856c24640a/resolve/main/training_args.bin
6.84 kB
- Xet hash:
- 627d4252f9e820215f4894d749a3db763b9e5df21a829adb4ceecb110d9cfe87
- Size of remote file:
- 6.84 kB
- SHA256:
- a8787535668976b80f466500c423e763748d0d412e95f0405e6cd4df4d6c4226
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