Instructions to use kokovova/a186af46-379d-4e2b-925a-408e60df4864 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use kokovova/a186af46-379d-4e2b-925a-408e60df4864 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/llama-3-8b") model = PeftModel.from_pretrained(base_model, "kokovova/a186af46-379d-4e2b-925a-408e60df4864") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from kokovova/a186af46-379d-4e2b-925a-408e60df4864: direct link, hf CLI and curl.
- Browser
- Download file 6.71 kB
-
https://huggingface.co/kokovova/a186af46-379d-4e2b-925a-408e60df4864/resolve/main/training_args.bin
- Command line
-
hf download hf://kokovova/a186af46-379d-4e2b-925a-408e60df4864/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/kokovova/a186af46-379d-4e2b-925a-408e60df4864/resolve/main/training_args.bin
6.71 kB
- Xet hash:
- b79ed31d093c9785182d92d21883a9496afa793adefd01f26dc87183efedf91c
- Size of remote file:
- 6.71 kB
- SHA256:
- 309850f22bcc87823928fc17a370cbc47282bfd3916a29e12c75147ef8a62fe4
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