Instructions to use kk-aivio/2e7d4628-1423-4d89-ad58-d4243e7b7905 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use kk-aivio/2e7d4628-1423-4d89-ad58-d4243e7b7905 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Hermes-3-Llama-3.1-8B") model = PeftModel.from_pretrained(base_model, "kk-aivio/2e7d4628-1423-4d89-ad58-d4243e7b7905") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from kk-aivio/2e7d4628-1423-4d89-ad58-d4243e7b7905: direct link, hf CLI and curl.
- Browser
- Download file 84 MB
-
https://huggingface.co/kk-aivio/2e7d4628-1423-4d89-ad58-d4243e7b7905/resolve/main/adapter_model.bin
- Command line
-
hf download hf://kk-aivio/2e7d4628-1423-4d89-ad58-d4243e7b7905/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/kk-aivio/2e7d4628-1423-4d89-ad58-d4243e7b7905/resolve/main/adapter_model.bin
84 MB
- Xet hash:
- 0671b8aae8cf7bf1ca5b4e878f4d5ee263a1e20ce9630b90e08c784198ce499d
- Size of remote file:
- 84 MB
- SHA256:
- ccccea03c596db3c05a39d4f4645f8f1de7f629bd9a35fcdbd7d2dd23cf03403
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