Instructions to use trangtrannnnn/81861e39-0c3b-43fb-9a27-df73e9c9787a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use trangtrannnnn/81861e39-0c3b-43fb-9a27-df73e9c9787a with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Artples/L-MChat-7b") model = PeftModel.from_pretrained(base_model, "trangtrannnnn/81861e39-0c3b-43fb-9a27-df73e9c9787a") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 330b1ca70d5b3320e68f4f2539fcf2c1a1e05ef892815aaf708a435ca1746661
- Size of remote file:
- 6.78 kB
- SHA256:
- 7e79051ca8a758ca16bd9a4ad05b90f5da001f6b8dc7f8246d21a4c812c1312c
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