Instructions to use 1-lock/aba53603-c1e7-44b1-a8d2-a464157f7d35 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use 1-lock/aba53603-c1e7-44b1-a8d2-a464157f7d35 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/aba53603-c1e7-44b1-a8d2-a464157f7d35") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from 1-lock/aba53603-c1e7-44b1-a8d2-a464157f7d35: direct link, hf CLI and curl.
- Browser
- Download file 6.84 kB
-
https://huggingface.co/1-lock/aba53603-c1e7-44b1-a8d2-a464157f7d35/resolve/main/training_args.bin
- Command line
-
hf download hf://1-lock/aba53603-c1e7-44b1-a8d2-a464157f7d35/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/1-lock/aba53603-c1e7-44b1-a8d2-a464157f7d35/resolve/main/training_args.bin
6.84 kB
- Xet hash:
- 9d950ef89ac66bc6f6ec99d1bf13da819d8533f4aeba110c305781bfec4dba5b
- Size of remote file:
- 6.84 kB
- SHA256:
- 768a829e7b9c01bd489d758600a12627cd7abe3e2ab22b9385b5a81bcb432b9d
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