Instructions to use aleegis10/c87c5e3d-711c-43d2-841a-095ee38d531b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use aleegis10/c87c5e3d-711c-43d2-841a-095ee38d531b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("The-matt/llama2_ko-7b_distinctive-snowflake-182_1060") model = PeftModel.from_pretrained(base_model, "aleegis10/c87c5e3d-711c-43d2-841a-095ee38d531b") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from aleegis10/c87c5e3d-711c-43d2-841a-095ee38d531b: direct link, hf CLI and curl.
- Browser
- Download file 640 MB
-
https://huggingface.co/aleegis10/c87c5e3d-711c-43d2-841a-095ee38d531b/resolve/main/adapter_model.bin
- Command line
-
hf download hf://aleegis10/c87c5e3d-711c-43d2-841a-095ee38d531b/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/aleegis10/c87c5e3d-711c-43d2-841a-095ee38d531b/resolve/main/adapter_model.bin
640 MB
- Xet hash:
- c3404a366214b9799d8b64d08e20756b38ff94b3a326eaaa5c04ad7e529bf48b
- Size of remote file:
- 640 MB
- SHA256:
- 9f65cef3ea0b135d3ea8859b14ec4f69fd678d7316e9b4c35ba9896c9bc93c29
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