Instructions to use dcbv/charluv-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dcbv/charluv-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("LLaMA2-13B-Tiefighter") model = PeftModel.from_pretrained(base_model, "dcbv/charluv-lora") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from dcbv/charluv-lora: direct link, hf CLI and curl.
- Browser
- Download file 2 GB
-
https://huggingface.co/dcbv/charluv-lora/resolve/main/adapter_model.bin
- Command line
-
hf download hf://dcbv/charluv-lora/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/dcbv/charluv-lora/resolve/main/adapter_model.bin
2 GB
- Xet hash:
- dad7d77dfc1e6b0aa0c6834a02e20cacb3c72bf5df5dec1174dc12039f8a2e2a
- Size of remote file:
- 2 GB
- SHA256:
- a28bb35807a1e0701ca619f722aba6f153335a231ca8fb59ee8c3af441f4bf98
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