Instructions to use dada22231/f0e02592-fed1-457a-aad1-7cd8fbbef9f4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dada22231/f0e02592-fed1-457a-aad1-7cd8fbbef9f4 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("HuggingFaceM4/tiny-random-LlamaForCausalLM") model = PeftModel.from_pretrained(base_model, "dada22231/f0e02592-fed1-457a-aad1-7cd8fbbef9f4") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from dada22231/f0e02592-fed1-457a-aad1-7cd8fbbef9f4: direct link, hf CLI and curl.
- Browser
- Download file 6.84 kB
-
https://huggingface.co/dada22231/f0e02592-fed1-457a-aad1-7cd8fbbef9f4/resolve/main/training_args.bin
- Command line
-
hf download hf://dada22231/f0e02592-fed1-457a-aad1-7cd8fbbef9f4/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/dada22231/f0e02592-fed1-457a-aad1-7cd8fbbef9f4/resolve/main/training_args.bin
6.84 kB
- Xet hash:
- b99d16b5755977f73bfe9111b03423feadfadc5b293cfca80c1d74410bf2280c
- Size of remote file:
- 6.84 kB
- SHA256:
- 28414fcb89081e483d190a598fccb27f6ba9fb7458cfaa3a76f311fa0ffc5415
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.