Instructions to use dada22231/3d3164c5-b8f8-4a60-affc-826cc3faa207 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dada22231/3d3164c5-b8f8-4a60-affc-826cc3faa207 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, "dada22231/3d3164c5-b8f8-4a60-affc-826cc3faa207") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 71059ae5f2f4a5978f90108741958f29bca31576cac4a8b46815990edb35338a
- Size of remote file:
- 336 MB
- SHA256:
- 66a9ec08ac537734e63cb4a9a55891b8697d7c45c6c0b89b8ebf3c7aae4eb9a8
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