Instructions to use nhung03/8a5e8a55-d5c2-4227-93e6-bf766c4fd3aa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nhung03/8a5e8a55-d5c2-4227-93e6-bf766c4fd3aa with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("microsoft/Phi-3-mini-4k-instruct") model = PeftModel.from_pretrained(base_model, "nhung03/8a5e8a55-d5c2-4227-93e6-bf766c4fd3aa") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cb1525643fae0bb6b7efd24a49695d8dd82923d3c5a2dc3c1bd497bde17e7fa1
- Size of remote file:
- 50.4 MB
- SHA256:
- 3ec7491b1a4eb947e9f6f2211f56aac4579c7aa44248e5a6bdc20390f57e793c
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