Instructions to use dzanbek/052e813f-70b6-4038-adb7-a826a5f24633 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dzanbek/052e813f-70b6-4038-adb7-a826a5f24633 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Nous-Hermes-2-Mistral-7B-DPO") model = PeftModel.from_pretrained(base_model, "dzanbek/052e813f-70b6-4038-adb7-a826a5f24633") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1fb4a6a7a0a65f4b6ad9aa50887facc5028a443c30233df48b6c6072c905bd71
- Size of remote file:
- 6.78 kB
- SHA256:
- a7494c717eade6cf0bfc66fe75e77aee37a9b60bbbb22bd5494229dac3c013c1
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