Instructions to use tarabukinivan/7237d99e-5040-4f58-906d-6864aa524904 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use tarabukinivan/7237d99e-5040-4f58-906d-6864aa524904 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-2-2b-it") model = PeftModel.from_pretrained(base_model, "tarabukinivan/7237d99e-5040-4f58-906d-6864aa524904") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0a444683c4c70e281e1d796483e91dce001df80c406d5b98b8452562beb2359d
- Size of remote file:
- 83.4 MB
- SHA256:
- de79a169c9b7c3db6620deb178bbce3fad1f258aad8eb418f848d3214b8b22ca
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