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:
- 5c84e113205bdf18ba57b7a4b652bca9d4f8d68f05da298cd29c818ec9937c22
- Size of remote file:
- 189 MB
- SHA256:
- 55d905c68a0a631af4230eb3cd3b82332cd23a6999a71ba8bf0a91a17595a38b
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