Instructions to use quannh197/5dd5a0fb-0035-4ea8-8e65-beaf15e840a6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use quannh197/5dd5a0fb-0035-4ea8-8e65-beaf15e840a6 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Hermes-2-Pro-Llama-3-8B") model = PeftModel.from_pretrained(base_model, "quannh197/5dd5a0fb-0035-4ea8-8e65-beaf15e840a6") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 71bf274bfe78072e075f1571caf1204de917fea521984418b69deacd12aa7c90
- Size of remote file:
- 43.1 MB
- SHA256:
- 615356630b7e40a9b2d58523a0f04f33486edd4ed9e727c86b115fdd0f2d3e40
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