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:
- d317e2f1d7e7ef7104e64b270ea511f4dda4feb52c1bfbd539ff3e4b974e29e5
- Size of remote file:
- 14.2 kB
- SHA256:
- ab113dd6b34c5e40abe76cb5c9662714bc0e4a97f5b37d5134da6a412a688812
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