Instructions to use mamung/5c36bf90-833a-4aa9-996b-95dea707aa90 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mamung/5c36bf90-833a-4aa9-996b-95dea707aa90 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, "mamung/5c36bf90-833a-4aa9-996b-95dea707aa90") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 50d3d62200a1cb1d705893d441e4682280158786b8cdc9e2568a6fa7e1a09b79
- Size of remote file:
- 671 MB
- SHA256:
- c28207602fafad9a248685272eecdb01b30dbd11950ffd8dd157e559bd0347a1
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