Instructions to use havinash-ai/7d68e859-8a3e-4096-ae8e-5d938eebb182 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use havinash-ai/7d68e859-8a3e-4096-ae8e-5d938eebb182 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-7b-it") model = PeftModel.from_pretrained(base_model, "havinash-ai/7d68e859-8a3e-4096-ae8e-5d938eebb182") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3b7afddf7992d0c77530b1ee5917eff1844fcafa8fcab2a9e2cd9f6b897af19b
- Size of remote file:
- 6.78 kB
- SHA256:
- acf1c1e87085985b18ebd489004dab9c1ddfdd1c7c340989e7af42eb8dd5f9a5
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