Instructions to use havinash-ai/3cbee2fe-6e5f-43d7-93eb-21377bdf07ce with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use havinash-ai/3cbee2fe-6e5f-43d7-93eb-21377bdf07ce 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, "havinash-ai/3cbee2fe-6e5f-43d7-93eb-21377bdf07ce") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4dd7ab86cec30deac16e9e1846f2f0fd1274b3a7587450be6137852d2a6e196f
- Size of remote file:
- 41.6 MB
- SHA256:
- 49f7f882cf294a63cbda779c85c0b23294cd1ca00544e849082819f96c954ceb
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