Instructions to use havinash-ai/b00a709a-60bb-4d7a-a4a0-aec24df22a51 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use havinash-ai/b00a709a-60bb-4d7a-a4a0-aec24df22a51 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/b00a709a-60bb-4d7a-a4a0-aec24df22a51") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7f9c376e19c9f9dbf16882924a9a8aac93099707c7ee931d3df9f96ef2eee8de
- Size of remote file:
- 41.6 MB
- SHA256:
- d98018a6b4db343e63e66a7a37dec85e16ccb62bc10761545cd22fed808e0ad7
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