Instructions to use Fischerboot/ll3-c3-lora-new with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Fischerboot/ll3-c3-lora-new with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Fischerboot/llama3-carlodda-v1") model = PeftModel.from_pretrained(base_model, "Fischerboot/ll3-c3-lora-new") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d9fce3bc17cdd2ef0c75ec901c664e2441565d08204dc2e4d29b6c4e302c0393
- Size of remote file:
- 671 MB
- SHA256:
- edbfa3e68e7bd2877c4f20deac32548ed2b790a140e509553f9d0647a92fff71
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.