Instructions to use dada22231/6c53732c-b110-4205-80dc-07c31fcc0444 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dada22231/6c53732c-b110-4205-80dc-07c31fcc0444 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Nous-Hermes-llama-2-7b") model = PeftModel.from_pretrained(base_model, "dada22231/6c53732c-b110-4205-80dc-07c31fcc0444") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0c580a7bbf19e5f68656bd2215f5588d4f24f3af9dcc0f7ca2efc14b608716a5
- Size of remote file:
- 640 MB
- SHA256:
- 82209303d278d3c86028b7bbe8fafb8e51159ba71f3c5b237cf7aca61bb58255
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