Instructions to use trangtrannnnn/8d5fcfd9-a910-4c70-a781-bd262755778c with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use trangtrannnnn/8d5fcfd9-a910-4c70-a781-bd262755778c with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("lmsys/vicuna-13b-v1.5") model = PeftModel.from_pretrained(base_model, "trangtrannnnn/8d5fcfd9-a910-4c70-a781-bd262755778c") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- db520699bea481ac7f82e9a9da19c9c9a12f4ab4c5b4666fdd15f15d6afb0bff
- Size of remote file:
- 6.78 kB
- SHA256:
- 2c94b29fc42aab5d222ae0f872fbc7c35d5e554507af0319f5687cd8a3695c46
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