Instructions to use vmpsergio/3b1673bd-e480-4503-824c-7cda3a5c3b46 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use vmpsergio/3b1673bd-e480-4503-824c-7cda3a5c3b46 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("EleutherAI/pythia-70m") model = PeftModel.from_pretrained(base_model, "vmpsergio/3b1673bd-e480-4503-824c-7cda3a5c3b46") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 325b23bbfcf60510e5d8a2c011ed1de66cf973697c615ec490eab4e6c299827f
- Size of remote file:
- 6.78 kB
- SHA256:
- c9f61ea2aed2a0b3249439c81c33011ebc8e1eb21688a92c76c34a448702caf3
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