Instructions to use johngreendr1/60a37ec5-3f44-4b1d-ab7d-718ec8811779 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use johngreendr1/60a37ec5-3f44-4b1d-ab7d-718ec8811779 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("teknium/OpenHermes-2.5-Mistral-7B") model = PeftModel.from_pretrained(base_model, "johngreendr1/60a37ec5-3f44-4b1d-ab7d-718ec8811779") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5928192b7c7289d36520e4c9e96cc7b9369e186335a8810a65cbad418f4677da
- Size of remote file:
- 1.34 GB
- SHA256:
- 16924cc037670d5dba1ea23b7f8f21ca6444aeea4f4c62c12c9ab1604b188124
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