Instructions to use beast33/aec93490-b5fc-4a7d-9037-a5813cf76ddd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use beast33/aec93490-b5fc-4a7d-9037-a5813cf76ddd with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/codegemma-2b") model = PeftModel.from_pretrained(base_model, "beast33/aec93490-b5fc-4a7d-9037-a5813cf76ddd") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 92c4bc9c7ed841542a26726d71ac33390f673bc2b542c7ab2ccd542f4f07efcf
- Size of remote file:
- 39.3 MB
- SHA256:
- c61aa162dc7f259f70b0b6dc32085e6e19a2b29d007844281943b645e8bed8b0
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