Instructions to use Vithika/llama2-qlora-finetunined-french-1900 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Vithika/llama2-qlora-finetunined-french-1900 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-french-1900") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 21d4b002ae371d6dd2412a2a93d8e8a767801b4d04e7ec1f1af40684e7e1e246
- Size of remote file:
- 134 MB
- SHA256:
- 5d72e280b7b3a29356add6680fef9bcbca64edc3ababe1c3dfa9ae0efc7173ac
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