Instructions to use mamung/29b84e13-2f1c-406f-9e7e-fd35b6e5ff49 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mamung/29b84e13-2f1c-406f-9e7e-fd35b6e5ff49 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("openlm-research/open_llama_3b") model = PeftModel.from_pretrained(base_model, "mamung/29b84e13-2f1c-406f-9e7e-fd35b6e5ff49") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7baee2f7be4838c972ab62d6a365246d93bd104ca0f608b2d6099b84fcbdceea
- Size of remote file:
- 6.78 kB
- SHA256:
- c3836ddb4a6ffabdb0a339929735e152b5fcf70dea1317ddb38ba3aec65aabc8
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