Instructions to use nhung03/ddf81ae0-fd56-49a8-a0be-da1168aca772 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nhung03/ddf81ae0-fd56-49a8-a0be-da1168aca772 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Mistral-Nemo-Instruct-2407") model = PeftModel.from_pretrained(base_model, "nhung03/ddf81ae0-fd56-49a8-a0be-da1168aca772") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eb3fab6b9882fe6913f236cdf534be6b23551e1b1377e53a507d3d71159238bc
- Size of remote file:
- 114 MB
- SHA256:
- 0b475fd6d30925a6146dcd7623db522846f34179d9a282c6e672f6ecece2a31c
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