Instructions to use demohong/9eb1d728-2118-43af-a749-034b95059a6e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use demohong/9eb1d728-2118-43af-a749-034b95059a6e 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, "demohong/9eb1d728-2118-43af-a749-034b95059a6e") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 46373e7ea52b45570836ee3c71cfce8629c8ad73ebca1a68d2e61cc0b20517b1
- Size of remote file:
- 84 MB
- SHA256:
- 5a9b08d7937d91b1ed0c8380c67d8cdb7fb549496bb3cad5c4cab852a9c968ad
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