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:
- aae8915a1f80f518d48d6d1af3c17e7b54f2063b44fc2cb638c9ad929f143149
- Size of remote file:
- 6.31 MB
- SHA256:
- e3e2d0bd833148674226bdd7ee10337602f3867815395d98b8b45f66449923c5
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