Instructions to use thangla01/521bcd67-9ca7-4f94-b0c3-b0b4f64e2a8e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use thangla01/521bcd67-9ca7-4f94-b0c3-b0b4f64e2a8e with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("lmsys/vicuna-7b-v1.5") model = PeftModel.from_pretrained(base_model, "thangla01/521bcd67-9ca7-4f94-b0c3-b0b4f64e2a8e") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 409b63d0f14ab5da7909ddcb93f85878ef0e4f19bfa91194b68ac5b45a5b6e87
- Size of remote file:
- 500 kB
- SHA256:
- 9e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347
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