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:
- 6ee4252483f69f77bfd5b403bc436612a4019bf8ce779b6b3c430ce20d6355cb
- Size of remote file:
- 6.78 kB
- SHA256:
- 4a377a0b944a9e9e27ff83d7a3b91b2ee2b773e411d65f0e825272b8c6d14308
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