Instructions to use vmpsergio/89761987-b232-472d-90d8-61292e37bf25 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use vmpsergio/89761987-b232-472d-90d8-61292e37bf25 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, "vmpsergio/89761987-b232-472d-90d8-61292e37bf25") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e81ce4ffa0d84026b96b552fda0aa4b555d467a598e4b60f64a78ad343037c1c
- Size of remote file:
- 6.78 kB
- SHA256:
- 67a7b105e1f4b3f14000826ed893c10b7fe8b93b9b6465bc3f14c51276dd82e3
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