Instructions to use aleegis/67010efc-a612-4ce2-9ccb-1f86489f5a3c with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use aleegis/67010efc-a612-4ce2-9ccb-1f86489f5a3c with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("JackFram/llama-160m") model = PeftModel.from_pretrained(base_model, "aleegis/67010efc-a612-4ce2-9ccb-1f86489f5a3c") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from aleegis/67010efc-a612-4ce2-9ccb-1f86489f5a3c: direct link, hf CLI and curl.
- Browser
- Download file 27.2 MB
-
https://huggingface.co/aleegis/67010efc-a612-4ce2-9ccb-1f86489f5a3c/resolve/main/adapter_model.bin
- Command line
-
hf download hf://aleegis/67010efc-a612-4ce2-9ccb-1f86489f5a3c/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/aleegis/67010efc-a612-4ce2-9ccb-1f86489f5a3c/resolve/main/adapter_model.bin
27.2 MB
- Xet hash:
- 755c1db8db7fb41a143e2864b624124c2cbc0d81ba82156f20e3a86084965ed7
- Size of remote file:
- 27.2 MB
- SHA256:
- fd00b39f31ebd2e1abe1b5f3d80744396aff6f01e3ea07b7d21e9f43a3127e2d
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