Instructions to use minhnguyennnnnn/f15c22f7-4612-4ee3-bb63-8efb4e250d8f with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use minhnguyennnnnn/f15c22f7-4612-4ee3-bb63-8efb4e250d8f with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("lcw99/zephykor-ko-7b-chang") model = PeftModel.from_pretrained(base_model, "minhnguyennnnnn/f15c22f7-4612-4ee3-bb63-8efb4e250d8f") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cafedf97e302897b0651436a8caf1c74ae6afcebb64e0a5c55a3cf2e61096d23
- Size of remote file:
- 84 MB
- SHA256:
- 30403eba992133041a3fc9a4b9b663a7f63f4c4c867b603a9ee4c41de212d8f7
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