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:
- 2b929d26116cbb7dfea9a3fdd983ce87febe1f4c29d8988c4eabae9c401fd412
- Size of remote file:
- 6.84 kB
- SHA256:
- 996f9319c0c3d90e7a9d865e178bc51d739fb97d14d270eb20cbeba4eef5f633
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