Instructions to use hongce-tech/openhermes-mistral-dpo-gptq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use hongce-tech/openhermes-mistral-dpo-gptq with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("TheBloke/OpenHermes-2-Mistral-7B-GPTQ") model = PeftModel.from_pretrained(base_model, "hongce-tech/openhermes-mistral-dpo-gptq") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 153b14b219c487c0c3e2793339c621750536c4f2d24d19ab26c141da9912ed8f
- Size of remote file:
- 13.6 MB
- SHA256:
- b4097ef9c252c00490381863af7152a65bedc8a2f4e38a202a90693d89b44ff4
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