Instructions to use lhong4759/7e7a5e39-8a29-44ed-bd79-67469f630bc8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use lhong4759/7e7a5e39-8a29-44ed-bd79-67469f630bc8 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("lmsys/vicuna-7b-v1.3") model = PeftModel.from_pretrained(base_model, "lhong4759/7e7a5e39-8a29-44ed-bd79-67469f630bc8") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 96918adcddee979d970d9165f46ca00fa7d416c9b9816331c290de3b3e83f2db
- Size of remote file:
- 80 MB
- SHA256:
- 4f1e13e738fbf709eb04586339249ab75c3e8a7ec3d7c1d41027eb8fc7babbec
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