Instructions to use Aivesa/91cc74e2-da3e-49d3-b1f2-e2b607dc1d24 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Aivesa/91cc74e2-da3e-49d3-b1f2-e2b607dc1d24 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("peft-internal-testing/tiny-dummy-qwen2") model = PeftModel.from_pretrained(base_model, "Aivesa/91cc74e2-da3e-49d3-b1f2-e2b607dc1d24") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from Aivesa/91cc74e2-da3e-49d3-b1f2-e2b607dc1d24: direct link, hf CLI and curl.
- Browser
- Download file 14.7 kB
-
https://huggingface.co/Aivesa/91cc74e2-da3e-49d3-b1f2-e2b607dc1d24/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://Aivesa/91cc74e2-da3e-49d3-b1f2-e2b607dc1d24/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/Aivesa/91cc74e2-da3e-49d3-b1f2-e2b607dc1d24/resolve/main/adapter_model.safetensors
14.7 kB
- Xet hash:
- 65a9748fd978e58a206e053cce955ed4cc0fe14e32dcf88392b0a133e5e26c3a
- Size of remote file:
- 14.7 kB
- SHA256:
- 98ef0d32aff075b0ab5b19e9c31679402b7c4235fd3698cf5d0017380d7bf7c3
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