Instructions to use dada22231/6f0d2e5b-1d77-4e06-9478-e20bfab370bb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dada22231/6f0d2e5b-1d77-4e06-9478-e20bfab370bb with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("MLP-KTLim/llama-3-Korean-Bllossom-8B") model = PeftModel.from_pretrained(base_model, "dada22231/6f0d2e5b-1d77-4e06-9478-e20bfab370bb") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1241e2475ba0c4e0e5040f1aef17476874511ab6e3f539a500ed1a1f13dc6597
- Size of remote file:
- 15 kB
- SHA256:
- e54a472b37f6bba44fda0bebab7623b7c17b18d0cce3ab17ce5eb16eb5fccfaf
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