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:
- 6e026136ce25551e35e9a09678dfb74fc1e10acd271b664d164ee0c4f7a6164d
- Size of remote file:
- 15 kB
- SHA256:
- c3d5a63540e4d651734cafc2cea838f55ae92bd586bf082f8597dd08e4ca7ab0
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