Instructions to use Vageesh1/LLAMAv2_AlPaca_Json with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Vageesh1/LLAMAv2_AlPaca_Json with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-7b-hf") model = PeftModel.from_pretrained(base_model, "Vageesh1/LLAMAv2_AlPaca_Json") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5040579bfdc9cd60a5201a8c9dc3f725799335b02ccedd6f175a7d3b924825b6
- Size of remote file:
- 33.6 MB
- SHA256:
- 363199f35dde2770a8a0ddc3b3dd9e34c0a17359dbb8950015b7d4e2ef52bb06
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