Instructions to use adammandic87/6af1ed4c-21cc-45df-8e37-236b857c9285 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use adammandic87/6af1ed4c-21cc-45df-8e37-236b857c9285 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("fxmarty/tiny-dummy-qwen2") model = PeftModel.from_pretrained(base_model, "adammandic87/6af1ed4c-21cc-45df-8e37-236b857c9285") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from adammandic87/6af1ed4c-21cc-45df-8e37-236b857c9285: direct link, hf CLI and curl.
- Browser
- Download file 21.4 kB
-
https://huggingface.co/adammandic87/6af1ed4c-21cc-45df-8e37-236b857c9285/resolve/main/adapter_model.bin
- Command line
-
hf download hf://adammandic87/6af1ed4c-21cc-45df-8e37-236b857c9285/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/adammandic87/6af1ed4c-21cc-45df-8e37-236b857c9285/resolve/main/adapter_model.bin
21.4 kB
- Xet hash:
- 5093131f0ac12461a46fed3ee3f72b8d23e58d3c44b18e8c3d9e20f955fd2cc1
- Size of remote file:
- 21.4 kB
- SHA256:
- 29d03ef402a4ac14a190ed0ab59672d5887c04954e603ce865b85198b1693dcb
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