Instructions to use dada22231/8e1125fa-262f-4c76-b23c-fb7b2fd6270e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dada22231/8e1125fa-262f-4c76-b23c-fb7b2fd6270e with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Llama-3.2-1B") model = PeftModel.from_pretrained(base_model, "dada22231/8e1125fa-262f-4c76-b23c-fb7b2fd6270e") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d9b0002aae8ccfd2d901ec54eaad6416334781ea4506bc94f3e86ce04b918353
- Size of remote file:
- 90.3 MB
- SHA256:
- 012e9b820ee49543a9ebff24379f61c6c40e1d36e4350955f5aa77d5ac16217f
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