Instructions to use devlocalhost/tinyllama-min-primary-secondary-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use devlocalhost/tinyllama-min-primary-secondary-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("PY007/TinyLlama-1.1B-Chat-v0.3") model = PeftModel.from_pretrained(base_model, "devlocalhost/tinyllama-min-primary-secondary-lora") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1c33e78ffd7a4abc4e193d68a74a857f71caab77665065dcbe6b95d12c6e289a
- Size of remote file:
- 4.52 MB
- SHA256:
- fd93d32bb3d9063e97b1cbbaa42b32c9f5184a1bc88867df25bd2c69248fab98
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.