Instructions to use nrishabh/llama3-8b-instruct-qlora-medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nrishabh/llama3-8b-instruct-qlora-medium with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("LoftQ/Meta-Llama-3-8B-Instruct-4bit-64rank") model = PeftModel.from_pretrained(base_model, "nrishabh/llama3-8b-instruct-qlora-medium") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9031b9d7803023218e47f22e8fee7f7642ebe174adc5a1c3a2548b727aa50b45
- Size of remote file:
- 5.05 kB
- SHA256:
- b5e393954fa13f306aefe6c4a4e118b95e3514b433e641bc88e0b8da131753af
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