Instructions to use adammandic87/a9cbb793-6a69-477f-9d7a-38d5701a3035 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use adammandic87/a9cbb793-6a69-477f-9d7a-38d5701a3035 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, "adammandic87/a9cbb793-6a69-477f-9d7a-38d5701a3035") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ef2b7fadc97fb6b3cf7c3cad18ed0f5aa3dfcfc77d5d58c24656cb3f13eca9da
- Size of remote file:
- 84 MB
- SHA256:
- 590c1b29da4020d5e44afc3a9179c904978ae2b563cb1d9b29c9e4e05c941b3d
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