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:
- a512547782317918bcd404ba961f11b96cc6513cfc85fa208fc289d3e6f20c7a
- Size of remote file:
- 1.06 kB
- SHA256:
- 2def2cd24154d8cecbaa07c36ae27e5ebb9b7273a78abfea27aa67c480e4ae2b
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