Instructions to use dimasik87/4ac67ab7-aaa5-46f9-b3dd-d935c7b307b8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dimasik87/4ac67ab7-aaa5-46f9-b3dd-d935c7b307b8 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("peft-internal-testing/tiny-dummy-qwen2") model = PeftModel.from_pretrained(base_model, "dimasik87/4ac67ab7-aaa5-46f9-b3dd-d935c7b307b8") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/training_args.bin from dimasik87/4ac67ab7-aaa5-46f9-b3dd-d935c7b307b8: direct link, hf CLI and curl.
- Browser
- Download file 6.84 kB
-
https://huggingface.co/dimasik87/4ac67ab7-aaa5-46f9-b3dd-d935c7b307b8/resolve/main/last-checkpoint/training_args.bin
- Command line
-
hf download hf://dimasik87/4ac67ab7-aaa5-46f9-b3dd-d935c7b307b8/last-checkpoint/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/dimasik87/4ac67ab7-aaa5-46f9-b3dd-d935c7b307b8/resolve/main/last-checkpoint/training_args.bin
6.84 kB
- Xet hash:
- 571d6e885caa97bcee2e444e7c291e2fede7c86c9ca7d88e9af4770b8f42ead0
- Size of remote file:
- 6.84 kB
- SHA256:
- 46fe00f1e04236950c1651df450c03d0b37a158487e9d4c187f30e05ef7452d4
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