Instructions to use 1-lock/dac18b37-3be7-4dc2-b933-a101dcd85545 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use 1-lock/dac18b37-3be7-4dc2-b933-a101dcd85545 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, "1-lock/dac18b37-3be7-4dc2-b933-a101dcd85545") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/training_args.bin from 1-lock/dac18b37-3be7-4dc2-b933-a101dcd85545: direct link, hf CLI and curl.
- Browser
- Download file 6.84 kB
-
https://huggingface.co/1-lock/dac18b37-3be7-4dc2-b933-a101dcd85545/resolve/main/last-checkpoint/training_args.bin
- Command line
-
hf download hf://1-lock/dac18b37-3be7-4dc2-b933-a101dcd85545/last-checkpoint/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/1-lock/dac18b37-3be7-4dc2-b933-a101dcd85545/resolve/main/last-checkpoint/training_args.bin
6.84 kB
- Xet hash:
- 433abdc5e7b578a9dacd7cbdd4d7fe72f421a63d1dca875702bf2eddaddc5320
- Size of remote file:
- 6.84 kB
- SHA256:
- fd202096d2a42c006224eb8dfe3082120fd9ef32f707465883a7903ac6a9eed7
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