Instructions to use dzanbek/cebcbad6-d889-4ef2-8f12-5c70683b8697 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dzanbek/cebcbad6-d889-4ef2-8f12-5c70683b8697 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5") model = PeftModel.from_pretrained(base_model, "dzanbek/cebcbad6-d889-4ef2-8f12-5c70683b8697") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f4f08f4619df68e612ce61ec598752f91e8ca52b1508453b0f184e26a9f8d815
- Size of remote file:
- 189 MB
- SHA256:
- ce7d56f9d90a95029e10ea5e9ac1e8f44c60c40071f190f064bd5f9b8eb8b32c
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