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:
- bb4879c03fae578808013c6247046c62163163d4ef83f9720029c9da28ae186b
- Size of remote file:
- 1.06 kB
- SHA256:
- ffd8c58e5d02492554dbaa495f8cf80dff41fabc0e1288cb2fd18a103d402219
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