Instructions to use laquythang/c63ae018-2509-4e3c-a76c-a24c918c49ef with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use laquythang/c63ae018-2509-4e3c-a76c-a24c918c49ef 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, "laquythang/c63ae018-2509-4e3c-a76c-a24c918c49ef") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from laquythang/c63ae018-2509-4e3c-a76c-a24c918c49ef: direct link, hf CLI and curl.
- Browser
- Download file 14.7 kB
-
https://huggingface.co/laquythang/c63ae018-2509-4e3c-a76c-a24c918c49ef/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://laquythang/c63ae018-2509-4e3c-a76c-a24c918c49ef/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/laquythang/c63ae018-2509-4e3c-a76c-a24c918c49ef/resolve/main/adapter_model.safetensors
14.7 kB
- Xet hash:
- 1d663d4763fe8c16cfa455f022e3091b8528da0cbf2f75f2f418a9d34371f652
- Size of remote file:
- 14.7 kB
- SHA256:
- 389246c7a9f4719cdd705eeeb671f896766f0592760e10f80e6e80d1814eebc4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.