Instructions to use Vithika/llama2-qlora-finetunined-code-text with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Vithika/llama2-qlora-finetunined-code-text with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("TinyPixel/Llama-2-7B-bf16-sharded") model = PeftModel.from_pretrained(base_model, "Vithika/llama2-qlora-finetunined-code-text") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3a9a4822ac265f0b88880cf7051827dc1e0fd40db17a707e7f4a72de9cec5c70
- Size of remote file:
- 134 MB
- SHA256:
- edf1a2a3fe19eabe0f8c373897f92753506e0427138df50c3dbbc3a8a1895237
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