Instructions to use nbninh/1ea92bb6-8722-4ecc-8816-441f58ac4f87 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nbninh/1ea92bb6-8722-4ecc-8816-441f58ac4f87 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2-0.5B-Instruct") model = PeftModel.from_pretrained(base_model, "nbninh/1ea92bb6-8722-4ecc-8816-441f58ac4f87") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2a328068c8c63707c336242b0ad2cfcf11731270d8f8f411ca68252437b627f5
- Size of remote file:
- 17.7 MB
- SHA256:
- cf92a9608e6a6775153479944273fe4f3322b8538b37655138d3d50756b82fc7
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