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:
- 19bef5ffe3ff5783dce8edc34a14f67808be839ec1aea2fce44a557977a969d2
- Size of remote file:
- 6.01 kB
- SHA256:
- 221c1c73c2f6e5abc702ed6ad70b63f030ca153ad4ced81da69d95da25b5d118
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.