Instructions to use BiniyamAjaw/llama-2-7b-finetuned-adapters with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use BiniyamAjaw/llama-2-7b-finetuned-adapters with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Llama-2-7b-hf") model = PeftModel.from_pretrained(base_model, "BiniyamAjaw/llama-2-7b-finetuned-adapters") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b31c4036631cd3aaa260d15263eb24cfa03f32fbcc41e920c88bba4a8e36941b
- Size of remote file:
- 9.99 GB
- SHA256:
- a8b9524bf811757e3ae42f0f0bb95ca8ede0ca3ba30b81b01ef2a09191a6eafb
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