Instructions to use vmpsergio/388fced2-7194-4f76-84cc-5abb47ae505f with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use vmpsergio/388fced2-7194-4f76-84cc-5abb47ae505f 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/388fced2-7194-4f76-84cc-5abb47ae505f") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fd5dada7216678e316a953b294d6e0aa255d795d3b875a4cd441f681bada17c1
- Size of remote file:
- 671 MB
- SHA256:
- cfe7279ea040f89af56c2efe8f97b5c3afa16342e2d181f6fd7da4f38e3726bd
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