Instructions to use dada22231/6bb2c487-2992-441b-90d1-b2fec57e5176 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dada22231/6bb2c487-2992-441b-90d1-b2fec57e5176 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Hermes-2-Pro-Mistral-7B") model = PeftModel.from_pretrained(base_model, "dada22231/6bb2c487-2992-441b-90d1-b2fec57e5176") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a8e21d226c1a63144936c6f3a42850f14065c9fe37c5f1b2665c3c83c761403b
- Size of remote file:
- 6.84 kB
- SHA256:
- 6b951b2c6deb50a960dac0348845e4f0bcdeb2a36a8cd0104856724c1e0fed86
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