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:
- 4bbef2af865469a6d2ec9ecd7ce0c28807ff2c87f3c00d2e54c2d44c60e671b1
- Size of remote file:
- 41.7 MB
- SHA256:
- 4170f0ca75df9c5b6aee5a7c8079dc4542ae165e5c6b0a375c6fa694d5dc713c
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