Instructions to use dada22231/57473b92-4192-49cb-9c74-0b29a21addf8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dada22231/57473b92-4192-49cb-9c74-0b29a21addf8 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("scb10x/llama-3-typhoon-v1.5-8b-instruct") model = PeftModel.from_pretrained(base_model, "dada22231/57473b92-4192-49cb-9c74-0b29a21addf8") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5952d22eae4b97d8930dd16b107d29d4adaaa89e72c9c7533760e81e463ea2c3
- Size of remote file:
- 336 MB
- SHA256:
- 3cfea6c2f4e01df55afe458ea112beab1c911af8f98db0ce3a7bfa1418e182c0
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