Instructions to use phungkhaccuong/fa71addc-951a-12d7-783c-32157f080bb4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use phungkhaccuong/fa71addc-951a-12d7-783c-32157f080bb4 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Hermes-2-Pro-Mistral-7B") model = PeftModel.from_pretrained(base_model, "phungkhaccuong/fa71addc-951a-12d7-783c-32157f080bb4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9abf755ba9849613c1b886c2b8c35ef75df8e85ace60e388e896c10aa8cca5fb
- Size of remote file:
- 83.9 MB
- SHA256:
- a4d0e2616267ec53c9702f8917adab21af65a13d74bd751b55ff88062463d6a8
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