Instructions to use 1-lock/dac18b37-3be7-4dc2-b933-a101dcd85545 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use 1-lock/dac18b37-3be7-4dc2-b933-a101dcd85545 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, "1-lock/dac18b37-3be7-4dc2-b933-a101dcd85545") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from 1-lock/dac18b37-3be7-4dc2-b933-a101dcd85545: direct link, hf CLI and curl.
- Browser
- Download file 48.6 kB
-
https://huggingface.co/1-lock/dac18b37-3be7-4dc2-b933-a101dcd85545/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://1-lock/dac18b37-3be7-4dc2-b933-a101dcd85545/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/1-lock/dac18b37-3be7-4dc2-b933-a101dcd85545/resolve/main/adapter_model.safetensors
48.6 kB
- Xet hash:
- 8c395008e0d497afbeb5a86179dde6bdd791ddbeaac0f142e3fbe707cbdd7caa
- Size of remote file:
- 48.6 kB
- SHA256:
- 3c081c6155cfd7f3e070d2aa12c4cf038e258ecbc308465d988375cdf622e45a
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