Instructions to use kk-aivio/4b965d6b-b099-462c-a0fa-8d0e5ec1fc3a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use kk-aivio/4b965d6b-b099-462c-a0fa-8d0e5ec1fc3a with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("echarlaix/tiny-random-mistral") model = PeftModel.from_pretrained(base_model, "kk-aivio/4b965d6b-b099-462c-a0fa-8d0e5ec1fc3a") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from kk-aivio/4b965d6b-b099-462c-a0fa-8d0e5ec1fc3a: direct link, hf CLI and curl.
- Browser
- Download file 6.78 kB
-
https://huggingface.co/kk-aivio/4b965d6b-b099-462c-a0fa-8d0e5ec1fc3a/resolve/main/training_args.bin
- Command line
-
hf download hf://kk-aivio/4b965d6b-b099-462c-a0fa-8d0e5ec1fc3a/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/kk-aivio/4b965d6b-b099-462c-a0fa-8d0e5ec1fc3a/resolve/main/training_args.bin
6.78 kB
- Xet hash:
- f08beedb567478c66e5750f90cb8920d03dc4576ff225649ce8fc32898203270
- Size of remote file:
- 6.78 kB
- SHA256:
- 1dbc672be1236a4dc0adf4d0832533f107558bf84bb6aa74229ae88154d85d4f
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