Instructions to use dimasik87/45076e52-eab9-4833-b617-c3aec1103800 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dimasik87/45076e52-eab9-4833-b617-c3aec1103800 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-2b-it") model = PeftModel.from_pretrained(base_model, "dimasik87/45076e52-eab9-4833-b617-c3aec1103800") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 39548a145a47e1cec1dc4388f9aaedb4ae6e29f53741b1beb99063d3ce455c0b
- Size of remote file:
- 34.4 MB
- SHA256:
- f559f2189f392b4555613965f089e7c4d300b41fbe080bf79da0d676e33ee7f0
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