Instructions to use 0x1202/87452ece-b414-41a5-92fe-520220d5df01 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use 0x1202/87452ece-b414-41a5-92fe-520220d5df01 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2-0.5B-Instruct") model = PeftModel.from_pretrained(base_model, "0x1202/87452ece-b414-41a5-92fe-520220d5df01") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from 0x1202/87452ece-b414-41a5-92fe-520220d5df01: direct link, hf CLI and curl.
- Browser
- Download file 6.84 kB
-
https://huggingface.co/0x1202/87452ece-b414-41a5-92fe-520220d5df01/resolve/49f19e1fc7acffa9faec58a351d9efcee2720dd2/training_args.bin
- Command line
-
hf download hf://0x1202/87452ece-b414-41a5-92fe-520220d5df01@49f19e1fc7acffa9faec58a351d9efcee2720dd2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/0x1202/87452ece-b414-41a5-92fe-520220d5df01/resolve/49f19e1fc7acffa9faec58a351d9efcee2720dd2/training_args.bin
6.84 kB
- Xet hash:
- b31f2d2b30109985cc9609ff6f08525ba2de65b7f0443388c559fa07b5e0c0dd
- Size of remote file:
- 6.84 kB
- SHA256:
- 61c5bcda0781c19fad4e78440f08408e68c21b3b19a0c1a89c8bd4aa813c40d7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.