Instructions to use quannh197/9321fefe-853f-483f-826c-4d079fcd3151 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use quannh197/9321fefe-853f-483f-826c-4d079fcd3151 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("aisingapore/llama3-8b-cpt-sea-lionv2.1-instruct") model = PeftModel.from_pretrained(base_model, "quannh197/9321fefe-853f-483f-826c-4d079fcd3151") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 59afd5118d795ed9325f134bfea0b3ee319e46ebe98a30d7dede25469e3e216e
- Size of remote file:
- 43.1 MB
- SHA256:
- e07f600fb597088a902196bf21c0d0d7fba2f5afa28d2b50b63125f1fa85e4de
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