Instructions to use aleegis/1031a985-5b6d-4489-a8cc-5b98f79b320c with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use aleegis/1031a985-5b6d-4489-a8cc-5b98f79b320c with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("jhflow/mistral7b-lora-multi-turn-v2") model = PeftModel.from_pretrained(base_model, "aleegis/1031a985-5b6d-4489-a8cc-5b98f79b320c") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 369ce9f629434da172d171bad8852e9a9ba19c7b38db1a238a898b9dc22f9036
- Size of remote file:
- 6.78 kB
- SHA256:
- 0c9ebded68d4d93446436d8d34aa57d8bb05d843f6b1229db0e5b2f96387a10a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.