Instructions to use ajtaltarabukin2022/bbacf562-5451-4c14-a79d-b6213663c3fa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ajtaltarabukin2022/bbacf562-5451-4c14-a79d-b6213663c3fa with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("dltjdgh0928/test_instruction") model = PeftModel.from_pretrained(base_model, "ajtaltarabukin2022/bbacf562-5451-4c14-a79d-b6213663c3fa") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from ajtaltarabukin2022/bbacf562-5451-4c14-a79d-b6213663c3fa: direct link, hf CLI and curl.
- Browser
- Download file 336 MB
-
https://huggingface.co/ajtaltarabukin2022/bbacf562-5451-4c14-a79d-b6213663c3fa/resolve/main/adapter_model.bin
- Command line
-
hf download hf://ajtaltarabukin2022/bbacf562-5451-4c14-a79d-b6213663c3fa/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/ajtaltarabukin2022/bbacf562-5451-4c14-a79d-b6213663c3fa/resolve/main/adapter_model.bin
336 MB
- Xet hash:
- 6d9e8baa804c7635d35b675e8c6910ef487acd805ed5eef6f905fe606d957e5e
- Size of remote file:
- 336 MB
- SHA256:
- 1ed3a2ee922cd82e1dd2481e29264ed381d7ce2dc61cb2d294b3ef2777d8667a
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